mistralai-mistral-nemo_9330

developer_uid: immaculate_possum_03470
submission_id: mistralai-mistral-nemo_9330_v123
model_name: nemo_base_1
model_group: mistralai/Mistral-Nemo-I
status: torndown
timestamp: 2024-09-26T23:49:17+00:00
num_battles: 3713
num_wins: 1845
celo_rating: 1244.59
family_friendly_score: 0.5706144008896302
family_friendly_standard_error: 0.008227684907971506
submission_type: basic
model_repo: mistralai/Mistral-Nemo-Instruct-2407
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
display_name: nemo_base_1
ineligible_reason: num_battles<5000
is_internal_developer: False
language_model: mistralai/Mistral-Nemo-Instruct-2407
model_size: 13B
ranking_group: single
us_pacific_date: 2024-09-26
win_ratio: 0.4969027740371667
generation_params: {'temperature': 0.95, 'top_p': 1.0, 'min_p': 0.075, 'top_k': 60, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n', '<|eot_id|>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name mistralai-mistral-nemo-9330-v123-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v123-mkmlizer to finish
mistralai-mistral-nemo-9330-v123-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v123-mkmlizer: ║     _____            __           __                                ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║       /___/                                                         ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  Version: 0.11.12                                                   ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  https://mk1.ai                                                     ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  belonging to:                                                      ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v123-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v123-mkmlizer: Downloaded to shared memory in 51.842s
mistralai-mistral-nemo-9330-v123-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp2izdixnc, device:0
mistralai-mistral-nemo-9330-v123-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v123-mkmlizer: quantized model in 35.791s
mistralai-mistral-nemo-9330-v123-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 87.633s
mistralai-mistral-nemo-9330-v123-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v123-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v123-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v123
mistralai-mistral-nemo-9330-v123-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v123/config.json
mistralai-mistral-nemo-9330-v123-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v123/special_tokens_map.json
mistralai-mistral-nemo-9330-v123-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v123/tokenizer_config.json
mistralai-mistral-nemo-9330-v123-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v123/tokenizer.json
mistralai-mistral-nemo-9330-v123-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v123/flywheel_model.0.safetensors
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Job mistralai-mistral-nemo-9330-v123-mkmlizer completed after 112.4s with status: succeeded
Stopping job with name mistralai-mistral-nemo-9330-v123-mkmlizer
Pipeline stage MKMLizer completed in 112.65s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.07s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service mistralai-mistral-nemo-9330-v123
Waiting for inference service mistralai-mistral-nemo-9330-v123 to be ready
Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name arushimgupta-peft-save-1-v8-mkmlizer
Waiting for job on arushimgupta-peft-save-1-v8-mkmlizer to finish
arushimgupta-peft-save-1-v8-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
arushimgupta-peft-save-1-v8-mkmlizer: ║     _____            __           __                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
arushimgupta-peft-save-1-v8-mkmlizer: ║       /___/                                                         ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Version: 0.11.12                                                   ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  https://mk1.ai                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  The license key for the current software has been verified as      ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  belonging to:                                                      ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Chai Research Corp.                                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
arushimgupta-peft-save-1-v8-mkmlizer: Downloaded to shared memory in 16.564s
arushimgupta-peft-save-1-v8-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpeumpr80p, device:0
arushimgupta-peft-save-1-v8-mkmlizer: Saving flywheel model at /dev/shm/model_cache
arushimgupta-peft-save-1-v8-mkmlizer: 
Loading 0:   0%|          | 0/1203 [00:00<?, ?it/s]Traceback (most recent call last):
arushimgupta-peft-save-1-v8-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
arushimgupta-peft-save-1-v8-mkmlizer:     cli()
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
arushimgupta-peft-save-1-v8-mkmlizer:     return self.main(*args, **kwargs)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
arushimgupta-peft-save-1-v8-mkmlizer:     rv = self.invoke(ctx)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
arushimgupta-peft-save-1-v8-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
arushimgupta-peft-save-1-v8-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
arushimgupta-peft-save-1-v8-mkmlizer:     return __callback(*args, **kwargs)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
arushimgupta-peft-save-1-v8-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
arushimgupta-peft-save-1-v8-mkmlizer:     flywheel.instrument(
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 93, in instrument
arushimgupta-peft-save-1-v8-mkmlizer:     compiler.save_pretrained(input_model_path, output_model_path, storage_format)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 23, in save_pretrained
arushimgupta-peft-save-1-v8-mkmlizer:     self.save_st_pretrained(input_model_path, output_model_path)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 38, in save_st_pretrained
arushimgupta-peft-save-1-v8-mkmlizer:     for name, tensor in model_iterator:
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/models/mistral.py", line 241, in tensor_merger
arushimgupta-peft-save-1-v8-mkmlizer:     for name, tensor in tensor_iterator:
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py", line 217, in tensor_compiler
arushimgupta-peft-save-1-v8-mkmlizer:     compiled_tensor = runtime.instrument(tensor, profile.value)
arushimgupta-peft-save-1-v8-mkmlizer: RuntimeError: CUDA error: invalid configuration argument
arushimgupta-peft-save-1-v8-mkmlizer: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
arushimgupta-peft-save-1-v8-mkmlizer: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
arushimgupta-peft-save-1-v8-mkmlizer: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
arushimgupta-peft-save-1-v8-mkmlizer: Exception raised from c10_cuda_check_implementation at ../c10/cuda/CUDAException.cpp:43 (most recent call first):
arushimgupta-peft-save-1-v8-mkmlizer: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x729257177f86 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x729257126d10 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, int, bool) + 0x118 (0x729257556f08 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #3: void at::native::gpu_kernel_impl<__nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> >(at::TensorIteratorBase&, __nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> const&) + 0x4de (0x729209b0aa2e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #4: void at::native::gpu_kernel<__nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> >(at::TensorIteratorBase&, __nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> const&) + 0x34b (0x729209b0b01b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #5: at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&) + 0x38c (0x729209ac9a0c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #6: at::native::copy_device_to_device(at::TensorIterator&, bool, bool) + 0xb25 (0x729209aca715 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #7: <unknown function> + 0x1910312 (0x729209acc312 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #8: <unknown function> + 0x1cbebff (0x72923f099bff in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #9: at::native::copy_(at::Tensor&, at::Tensor const&, bool) + 0x62 (0x72923f09b5a2 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #10: at::_ops::copy_::call(at::Tensor&, at::Tensor const&, bool) + 0x15c (0x72923fe5635c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #11: at::native::_to_copy(at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0x1e01 (0x72923f3b96b1 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #12: <unknown function> + 0x2e19f8b (0x7292401f4f8b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #13: at::_ops::_to_copy::redispatch(c10::DispatchKeySet, at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0xf5 (0x72923f8fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #14: <unknown function> + 0x2c58a33 (0x729240033a33 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #15: at::_ops::_to_copy::redispatch(c10::DispatchKeySet, at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0xf5 (0x72923f8fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #16: <unknown function> + 0x470df1f (0x729241ae8f1f in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #17: <unknown function> + 0x470e35e (0x729241ae935e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #18: at::_ops::_to_copy::call(at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0x1eb (0x72923f98d68b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #19: at::native::to(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0xa2 (0x72923f3b6182 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #20: <unknown function> + 0x301e3b0 (0x7292403f93b0 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #21: at::_ops::to_dtype::call(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0x178 (0x72923fb3d258 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #22: mkodec::instrument(at::Tensor, int) + 0x4b (0x72917b9c81ab in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #23: <unknown function> + 0x981e2 (0x72917b9b01e2 in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #24: <unknown function> + 0xa7b9b (0x72917b9bfb9b in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #25: python3() [0x4fd907]
arushimgupta-peft-save-1-v8-mkmlizer: <omitting python frames>
arushimgupta-peft-save-1-v8-mkmlizer: frame #28: python3() [0x5112cf]
arushimgupta-peft-save-1-v8-mkmlizer: frame #30: python3() [0x5112cf]
arushimgupta-peft-save-1-v8-mkmlizer: frame #43: python3() [0x5095ce]
arushimgupta-peft-save-1-v8-mkmlizer: frame #50: python3() [0x509857]
arushimgupta-peft-save-1-v8-mkmlizer: frame #54: python3() [0x5cf913]
arushimgupta-peft-save-1-v8-mkmlizer: frame #57: python3() [0x5951c2]
arushimgupta-peft-save-1-v8-mkmlizer: frame #59: python3() [0x5c5ef7]
arushimgupta-peft-save-1-v8-mkmlizer: frame #60: python3() [0x5c1030]
arushimgupta-peft-save-1-v8-mkmlizer: frame #61: python3() [0x459781]
arushimgupta-peft-save-1-v8-mkmlizer: 
                                                   
Job arushimgupta-peft-save-1-v8-mkmlizer completed after 45.85s with status: failed
Stopping job with name arushimgupta-peft-save-1-v8-mkmlizer
%s, retrying in %s seconds...
Starting job with name arushimgupta-peft-save-1-v8-mkmlizer
Waiting for job on arushimgupta-peft-save-1-v8-mkmlizer to finish
arushimgupta-peft-save-1-v8-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
arushimgupta-peft-save-1-v8-mkmlizer: ║     _____            __           __                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
arushimgupta-peft-save-1-v8-mkmlizer: ║       /___/                                                         ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Version: 0.11.12                                                   ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  https://mk1.ai                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  The license key for the current software has been verified as      ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  belonging to:                                                      ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Chai Research Corp.                                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
arushimgupta-peft-save-1-v8-mkmlizer: Downloaded to shared memory in 17.558s
arushimgupta-peft-save-1-v8-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpt83jcxv5, device:0
arushimgupta-peft-save-1-v8-mkmlizer: Saving flywheel model at /dev/shm/model_cache
arushimgupta-peft-save-1-v8-mkmlizer: 
Loading 0:   0%|          | 0/1203 [00:00<?, ?it/s]Traceback (most recent call last):
arushimgupta-peft-save-1-v8-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
arushimgupta-peft-save-1-v8-mkmlizer:     cli()
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
arushimgupta-peft-save-1-v8-mkmlizer:     return self.main(*args, **kwargs)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
arushimgupta-peft-save-1-v8-mkmlizer:     rv = self.invoke(ctx)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
arushimgupta-peft-save-1-v8-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
arushimgupta-peft-save-1-v8-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
arushimgupta-peft-save-1-v8-mkmlizer:     return __callback(*args, **kwargs)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
arushimgupta-peft-save-1-v8-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
arushimgupta-peft-save-1-v8-mkmlizer:     flywheel.instrument(
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 93, in instrument
arushimgupta-peft-save-1-v8-mkmlizer:     compiler.save_pretrained(input_model_path, output_model_path, storage_format)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 23, in save_pretrained
arushimgupta-peft-save-1-v8-mkmlizer:     self.save_st_pretrained(input_model_path, output_model_path)
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 38, in save_st_pretrained
arushimgupta-peft-save-1-v8-mkmlizer:     for name, tensor in model_iterator:
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/models/mistral.py", line 241, in tensor_merger
arushimgupta-peft-save-1-v8-mkmlizer:     for name, tensor in tensor_iterator:
arushimgupta-peft-save-1-v8-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py", line 217, in tensor_compiler
arushimgupta-peft-save-1-v8-mkmlizer:     compiled_tensor = runtime.instrument(tensor, profile.value)
arushimgupta-peft-save-1-v8-mkmlizer: RuntimeError: CUDA error: invalid configuration argument
arushimgupta-peft-save-1-v8-mkmlizer: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
arushimgupta-peft-save-1-v8-mkmlizer: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
arushimgupta-peft-save-1-v8-mkmlizer: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
arushimgupta-peft-save-1-v8-mkmlizer: Exception raised from c10_cuda_check_implementation at ../c10/cuda/CUDAException.cpp:43 (most recent call first):
arushimgupta-peft-save-1-v8-mkmlizer: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7beb27777f86 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x7beb27726d10 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, int, bool) + 0x118 (0x7beb27b69f08 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #3: void at::native::gpu_kernel_impl<__nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> >(at::TensorIteratorBase&, __nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> const&) + 0x4de (0x7beada50aa2e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #4: void at::native::gpu_kernel<__nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> >(at::TensorIteratorBase&, __nv_hdl_wrapper_t<false, true, false, __nv_dl_tag<void (*)(at::TensorIteratorBase&), &at::native::direct_copy_kernel_cuda, 18u>, c10::Half (c10::Half)> const&) + 0x34b (0x7beada50b01b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #5: at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&) + 0x38c (0x7beada4c9a0c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #6: at::native::copy_device_to_device(at::TensorIterator&, bool, bool) + 0xb25 (0x7beada4ca715 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #7: <unknown function> + 0x1910312 (0x7beada4cc312 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #8: <unknown function> + 0x1cbebff (0x7beb0fa99bff in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #9: at::native::copy_(at::Tensor&, at::Tensor const&, bool) + 0x62 (0x7beb0fa9b5a2 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #10: at::_ops::copy_::call(at::Tensor&, at::Tensor const&, bool) + 0x15c (0x7beb1085635c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #11: at::native::_to_copy(at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0x1e01 (0x7beb0fdb96b1 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #12: <unknown function> + 0x2e19f8b (0x7beb10bf4f8b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #13: at::_ops::_to_copy::redispatch(c10::DispatchKeySet, at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0xf5 (0x7beb102fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #14: <unknown function> + 0x2c58a33 (0x7beb10a33a33 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #15: at::_ops::_to_copy::redispatch(c10::DispatchKeySet, at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0xf5 (0x7beb102fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #16: <unknown function> + 0x470df1f (0x7beb124e8f1f in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #17: <unknown function> + 0x470e35e (0x7beb124e935e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #18: at::_ops::_to_copy::call(at::Tensor const&, std::optional<c10::ScalarType>, std::optional<c10::Layout>, std::optional<c10::Device>, std::optional<bool>, bool, std::optional<c10::MemoryFormat>) + 0x1eb (0x7beb1038d68b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #19: at::native::to(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0xa2 (0x7beb0fdb6182 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #20: <unknown function> + 0x301e3b0 (0x7beb10df93b0 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #21: at::_ops::to_dtype::call(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0x178 (0x7beb1053d258 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #22: mkodec::instrument(at::Tensor, int) + 0x4b (0x7bea4c2c81ab in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #23: <unknown function> + 0x981e2 (0x7bea4c2b01e2 in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #24: <unknown function> + 0xa7b9b (0x7bea4c2bfb9b in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v8-mkmlizer: frame #25: python3() [0x4fd907]
arushimgupta-peft-save-1-v8-mkmlizer: <omitting python frames>
arushimgupta-peft-save-1-v8-mkmlizer: frame #28: python3() [0x5112cf]
arushimgupta-peft-save-1-v8-mkmlizer: frame #30: python3() [0x5112cf]
arushimgupta-peft-save-1-v8-mkmlizer: frame #43: python3() [0x5095ce]
arushimgupta-peft-save-1-v8-mkmlizer: frame #50: python3() [0x509857]
arushimgupta-peft-save-1-v8-mkmlizer: frame #54: python3() [0x5cf913]
arushimgupta-peft-save-1-v8-mkmlizer: frame #57: python3() [0x5951c2]
arushimgupta-peft-save-1-v8-mkmlizer: frame #59: python3() [0x5c5ef7]
arushimgupta-peft-save-1-v8-mkmlizer: frame #60: python3() [0x5c1030]
arushimgupta-peft-save-1-v8-mkmlizer: frame #61: python3() [0x459781]
arushimgupta-peft-save-1-v8-mkmlizer: 
                                                   
Job arushimgupta-peft-save-1-v8-mkmlizer completed after 58.65s with status: failed
Stopping job with name arushimgupta-peft-save-1-v8-mkmlizer
%s, retrying in %s seconds...
Starting job with name arushimgupta-peft-save-1-v8-mkmlizer
Waiting for job on arushimgupta-peft-save-1-v8-mkmlizer to finish
Inference service mistralai-mistral-nemo-9330-v123 ready after 220.5022361278534s
Pipeline stage MKMLDeployer completed in 220.80s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.250133991241455s
Received healthy response to inference request in 2.0642929077148438s
arushimgupta-peft-save-1-v8-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
arushimgupta-peft-save-1-v8-mkmlizer: ║     _____            __           __                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
arushimgupta-peft-save-1-v8-mkmlizer: ║       /___/                                                         ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Version: 0.11.12                                                   ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  https://mk1.ai                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  The license key for the current software has been verified as      ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  belonging to:                                                      ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Chai Research Corp.                                                ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
arushimgupta-peft-save-1-v8-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
arushimgupta-peft-save-1-v8-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v8-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Received healthy response to inference request in 1.8556797504425049s
Received healthy response to inference request in 2.179812431335449s
Received healthy response to inference request in 2.292917251586914s
5 requests
0 failed requests
5th percentile: 1.8974023818969727
10th percentile: 1.9391250133514404
20th percentile: 2.022570276260376
30th percentile: 2.087396812438965
40th percentile: 2.133604621887207
50th percentile: 2.179812431335449
60th percentile: 2.2079410552978516
70th percentile: 2.236069679260254
80th percentile: 2.2586906433105467
90th percentile: 2.2758039474487304
95th percentile: 2.2843605995178224
99th percentile: 2.2912059211730957
mean time: 2.128567266464233
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