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Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC / logs.txt
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/opt/conda/envs/py310/bin/python -m mlc_llm gen_config /models/Mixtral-8x7B-Instruct-v0.1 --quantization q4f32_1 --conv-template mistral_default --output /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC
[2024-06-06 22:21:44] INFO auto_config.py:116: Found model configuration: /models/Mixtral-8x7B-Instruct-v0.1/config.json
[2024-06-06 22:21:44] INFO auto_config.py:154: Found model type: mixtral. Use `--model-type` to override.
[2024-06-06 22:21:44] INFO llama_model.py:52: context_window_size not found in config.json. Falling back to max_position_embeddings (32768)
[2024-06-06 22:21:44] INFO llama_model.py:72: prefill_chunk_size defaults to 2048
[2024-06-06 22:21:44] INFO config.py:107: Overriding max_batch_size from 1 to 80
[2024-06-06 22:21:44] INFO gen_config.py:143: [generation_config.json] Setting bos_token_id: 1
[2024-06-06 22:21:44] INFO gen_config.py:143: [generation_config.json] Setting eos_token_id: 2
[2024-06-06 22:21:44] INFO gen_config.py:155: Found tokenizer config: /models/Mixtral-8x7B-Instruct-v0.1/tokenizer.model. Copying to /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC/tokenizer.model
[2024-06-06 22:21:44] INFO gen_config.py:155: Found tokenizer config: /models/Mixtral-8x7B-Instruct-v0.1/tokenizer.json. Copying to /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC/tokenizer.json
[2024-06-06 22:21:44] INFO gen_config.py:157: Not found tokenizer config: /models/Mixtral-8x7B-Instruct-v0.1/vocab.json
[2024-06-06 22:21:44] INFO gen_config.py:157: Not found tokenizer config: /models/Mixtral-8x7B-Instruct-v0.1/merges.txt
[2024-06-06 22:21:44] INFO gen_config.py:157: Not found tokenizer config: /models/Mixtral-8x7B-Instruct-v0.1/added_tokens.json
[2024-06-06 22:21:44] INFO gen_config.py:155: Found tokenizer config: /models/Mixtral-8x7B-Instruct-v0.1/tokenizer_config.json. Copying to /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC/tokenizer_config.json
[2024-06-06 22:21:44] INFO gen_config.py:216: Detected tokenizer info: {'token_postproc_method': 'byte_fallback', 'prepend_space_in_encode': True, 'strip_space_in_decode': True}
[2024-06-06 22:21:44] INFO gen_config.py:32: [System default] Setting pad_token_id: 0
[2024-06-06 22:21:44] INFO gen_config.py:32: [System default] Setting temperature: 1.0
[2024-06-06 22:21:44] INFO gen_config.py:32: [System default] Setting presence_penalty: 0.0
[2024-06-06 22:21:44] INFO gen_config.py:32: [System default] Setting frequency_penalty: 0.0
[2024-06-06 22:21:44] INFO gen_config.py:32: [System default] Setting repetition_penalty: 1.0
[2024-06-06 22:21:44] INFO gen_config.py:32: [System default] Setting top_p: 1.0
[2024-06-06 22:21:44] INFO gen_config.py:223: Dumping configuration file to: /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC/mlc-chat-config.json
/opt/conda/envs/py310/bin/python -m mlc_llm convert_weight /models/Mixtral-8x7B-Instruct-v0.1 --quantization q4f32_1 --output /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC
[2024-06-06 22:21:46] INFO auto_config.py:116: Found model configuration: /models/Mixtral-8x7B-Instruct-v0.1/config.json
[2024-06-06 22:21:47] INFO auto_device.py:79: Found device: cuda:0
[2024-06-06 22:21:49] INFO auto_device.py:88: Not found device: rocm:0
[2024-06-06 22:21:50] INFO auto_device.py:88: Not found device: metal:0
[2024-06-06 22:21:52] INFO auto_device.py:79: Found device: vulkan:0
[2024-06-06 22:21:52] INFO auto_device.py:79: Found device: vulkan:1
[2024-06-06 22:21:52] INFO auto_device.py:79: Found device: vulkan:2
[2024-06-06 22:21:52] INFO auto_device.py:79: Found device: vulkan:3
[2024-06-06 22:21:53] INFO auto_device.py:88: Not found device: opencl:0
[2024-06-06 22:21:53] INFO auto_device.py:35: Using device: cuda:0
[2024-06-06 22:21:53] INFO auto_weight.py:71: Finding weights in: /models/Mixtral-8x7B-Instruct-v0.1
[2024-06-06 22:21:53] INFO auto_weight.py:137: Not found Huggingface PyTorch
[2024-06-06 22:21:53] INFO auto_weight.py:144: Found source weight format: huggingface-safetensor. Source configuration: /models/Mixtral-8x7B-Instruct-v0.1/model.safetensors.index.json
[2024-06-06 22:21:53] INFO auto_weight.py:107: Using source weight configuration: /models/Mixtral-8x7B-Instruct-v0.1/model.safetensors.index.json. Use `--source` to override.
[2024-06-06 22:21:53] INFO auto_weight.py:111: Using source weight format: huggingface-safetensor. Use `--source-format` to override.
[2024-06-06 22:21:53] INFO auto_config.py:154: Found model type: mixtral. Use `--model-type` to override.
[2024-06-06 22:21:53] INFO llama_model.py:52: context_window_size not found in config.json. Falling back to max_position_embeddings (32768)
[2024-06-06 22:21:53] INFO llama_model.py:72: prefill_chunk_size defaults to 2048
Weight conversion with arguments:
--config /models/Mixtral-8x7B-Instruct-v0.1/config.json
--quantization GroupQuantize(name='q4f32_1', kind='group-quant', group_size=32, quantize_dtype='int4', storage_dtype='uint32', model_dtype='float32', linear_weight_layout='NK', quantize_embedding=True, quantize_final_fc=True, num_elem_per_storage=8, num_storage_per_group=4, max_int_value=7)
--model-type mixtral
--device cuda:0
--source /models/Mixtral-8x7B-Instruct-v0.1/model.safetensors.index.json
--source-format huggingface-safetensor
--output /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC
Start storing to cache /models/mlc-delivery/hf/mlc-ai/Mixtral-8x7B-Instruct-v0.1-q4f32_1-MLC
0%| | 0/227 [00:00<?, ?it/s] [2024-06-06 22:23:27] INFO huggingface_loader.py:185: Loading HF parameters from: /models/Mixtral-8x7B-Instruct-v0.1/model-00019-of-00019.safetensors
0%| | 0/227 [00:00<?, ?it/s] [2024-06-06 22:23:32] INFO group_quantization.py:217: Compiling quantize function for key: ((32000, 4096), float32, cuda, axis=1, output_transpose=False)
0%| | 0/227 [00:05<?, ?it/s] [2024-06-06 22:23:33] INFO huggingface_loader.py:167: [Quantized] Parameter: "lm_head.q_weight", shape: (32000, 512), dtype: uint32
0%| | 0/227 [00:06<?, ?it/s] [2024-06-06 22:23:33] INFO huggingface_loader.py:167: [Quantized] Parameter: "lm_head.q_scale", shape: (32000, 128), dtype: float32
0%| | 0/227 [00:06<?, ?it/s] 0%| | 1/227 [00:06<23:41, 6.29s/it] [2024-06-06 22:23:33] INFO huggingface_loader.py:185: Loading HF parameters from: /models/Mixtral-8x7B-Instruct-v0.1/model-00018-of-00019.safetensors
0%| | 1/227 [00:06<23:41, 6.29s/it] [2024-06-06 22:23:45] INFO group_quantization.py:217: Compiling quantize function for key: ((8, 28672, 4096), float32, cuda, axis=2, output_transpose=False)
0%| | 1/227 [00:18<23:41, 6.29s/it] [2024-06-06 22:23:46] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.layers.30.moe.e1_e3.q_weight", shape: (8, 28672, 512), dtype: uint32
0%| | 1/227 [00:18<23:41, 6.29s/it] [2024-06-06 22:23:47] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.layers.30.moe.e1_e3.q_scale", shape: (8, 28672, 128), dtype: float32
0%| | 1/227 [00:19<23:41, 6.29s/it] 1%| | 2/227 [00:20<40:15, 10.74s/it] [2024-06-06 22:23:48] INFO group_quantization.py:217: Compiling quantize function for key: ((8, 4096, 14336), float32, cuda, axis=2, output_transpose=False)
1%| | 2/227 [00:20<40:15, 10.74s/it] [2024-06-06 22:23:48] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.layers.30.moe.e2.q_weight", shape: (8, 4096, 1792), dtype: uint32
1%| | 2/227 [00:21<40:15, 10.74s/it] [2024-06-06 22:23:49] INFO huggingface_loader.py:167: [Quantized] Parameter: "model.layers.30.moe.e2.q_scale", shape: (8, 4096, 448), dtype: float32
1%| | 2/227 [00:21<40:15, 10.74s/it] 1%|▏ | 3/227 [00:22<24:57, 6.68s/it] [2024-06-06 22:23:49] INFO huggingface_loader.py:175: [Not quantized] Parameter: "model.layers.30.input_layernorm.weight", shape: (4096,), dtype: float32
1%|▏ | 3/227 [00:22<24:57, 6.68s/it] [2024-06-06 22:23:49] INFO huggingface_loader.py:175: [Not quantized] Parameter: "model.layers.30.post_attention_layernorm.weight", shape: (4096,), dtype: float32
1%|▏ | 3/227 [00:22<24:57, 6.68s/it] 2%|▏ | 5/227 [00:29<21:48, 5.89s/it]
Traceback (most recent call last):
File "/opt/conda/envs/py310/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/opt/conda/envs/py310/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/__main__.py", line 64, in <module>
main()
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/__main__.py", line 37, in main
cli.main(sys.argv[2:])
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/cli/convert_weight.py", line 88, in main
convert_weight(
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/interface/convert_weight.py", line 181, in convert_weight
_convert_args(args)
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/interface/convert_weight.py", line 145, in _convert_args
tvmjs.dump_ndarray_cache(
File "/opt/conda/envs/py310/lib/python3.10/site-packages/tvm/contrib/tvmjs.py", line 272, in dump_ndarray_cache
for k, origin_v in param_generator:
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/interface/convert_weight.py", line 129, in _param_generator
for name, param in loader.load(device=args.device, preshard_funcs=preshard_funcs):
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/loader/huggingface_loader.py", line 118, in load
param = self._load_mlc_param(mlc_name, device=device)
File "/opt/conda/envs/py310/lib/python3.10/site-packages/mlc_llm/loader/huggingface_loader.py", line 157, in _load_mlc_param
return as_ndarray(param, device=device)
File "/opt/conda/envs/py310/lib/python3.10/site-packages/tvm/runtime/ndarray.py", line 675, in array
return empty(arr.shape, arr.dtype, device, mem_scope).copyfrom(arr)
File "/opt/conda/envs/py310/lib/python3.10/site-packages/tvm/runtime/ndarray.py", line 431, in empty
arr = _ffi_api.TVMArrayAllocWithScope(shape, dtype, device, mem_scope)
File "tvm/_ffi/_cython/./packed_func.pxi", line 332, in tvm._ffi._cy3.core.PackedFuncBase.__call__
File "tvm/_ffi/_cython/./packed_func.pxi", line 277, in tvm._ffi._cy3.core.FuncCall
File "tvm/_ffi/_cython/./base.pxi", line 182, in tvm._ffi._cy3.core.CHECK_CALL
File "/opt/conda/envs/py310/lib/python3.10/site-packages/tvm/_ffi/base.py", line 481, in raise_last_ffi_error
raise py_err
tvm.error.InternalError: Traceback (most recent call last):
5: _ZN3tvm7runtime13PackedFun
4: tvm::runtime::TypedPackedFunc<tvm::runtime::NDArray (tvm::runtime::ShapeTuple, DLDataType, DLDevice, tvm::runtime::Optional<tvm::runtime::String>)>::AssignTypedLambda<tvm::runtime::NDArray (*)(tvm::runtime::ShapeTuple, DLDataType, DLDevice, tvm::runtime::Optional<tvm::runtime::String>)>(tvm::runtime::NDArray (*)(tvm::runtime::ShapeTuple, DLDataType, DLDevice, tvm::runtime::Optional<tvm::runtime::String>), std::__cxx11::basic_string<char, std::char_traits<char>, std::allocator<char> >)::{lambda(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*)#1}::operator()(tvm::runtime::TVMArgs const&, tvm::runtime::TVMRetValue*) const
3: tvm::runtime::NDArray::Empty(tvm::runtime::ShapeTuple, DLDataType, DLDevice, tvm::runtime::Optional<tvm::runtime::String>)
2: tvm::runtime::DeviceAPI::AllocDataSpace(DLDevice, int, long const*, DLDataType, tvm::runtime::Optional<tvm::runtime::String>)
1: tvm::runtime::CUDADeviceAPI::AllocDataSpace(DLDevice, unsigned long, unsigned long, DLDataType)
0: _ZN3tvm7runtime6deta
File "/workspace/tvm/src/runtime/cuda/cuda_device_api.cc", line 145
InternalError: Check failed: (e == cudaSuccess || e == cudaErrorCudartUnloading) is false: CUDA: out of memory