chaiml-0926-nemo-virgo-t_3956

developer_uid: azuruce
submission_id: chaiml-0926-nemo-virgo-t_3956_v7
model_name: chaiml-0926-nemo-virgo-t_3956_v7
model_group: ChaiML/0926-nemo-virgo-t
status: torndown
timestamp: 2024-09-26T23:38:58+00:00
num_battles: 3304
num_wins: 1649
celo_rating: 1249.91
family_friendly_score: 0.5736940298507462
family_friendly_standard_error: 0.00869967927886753
submission_type: basic
model_repo: ChaiML/0926-nemo-virgo-top-safe-bot-1edit
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
display_name: chaiml-0926-nemo-virgo-t_3956_v7
ineligible_reason: num_battles<5000
is_internal_developer: True
language_model: ChaiML/0926-nemo-virgo-top-safe-bot-1edit
model_size: 13B
ranking_group: single
us_pacific_date: 2024-09-26
win_ratio: 0.49909200968523004
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': '', 'prompt_template': '', '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 chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer
Waiting for job on chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer to finish
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-v121-mkmlizer
Waiting for job on mistralai-mistral-nemo-9330-v121-mkmlizer to finish
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║     _____            __           __                                ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║       /___/                                                         ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  Version: 0.11.12                                                   ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  https://mk1.ai                                                     ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  The license key for the current software has been verified as      ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  belonging to:                                                      ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  Chai Research Corp.                                                ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ║                                                                     ║
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v121-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
mistralai-mistral-nemo-9330-v121-mkmlizer: ║     _____            __           __                                ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║       /___/                                                         ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  Version: 0.11.12                                                   ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  https://mk1.ai                                                     ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  The license key for the current software has been verified as      ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  belonging to:                                                      ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  Chai Research Corp.                                                ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ║                                                                     ║
mistralai-mistral-nemo-9330-v121-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
mistralai-mistral-nemo-9330-v121-mkmlizer: Downloaded to shared memory in 48.849s
mistralai-mistral-nemo-9330-v121-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpt_mjcyku, device:0
mistralai-mistral-nemo-9330-v121-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v121-mkmlizer: quantized model in 37.829s
mistralai-mistral-nemo-9330-v121-mkmlizer: Processed model mistralai/Mistral-Nemo-Instruct-2407 in 86.678s
mistralai-mistral-nemo-9330-v121-mkmlizer: creating bucket guanaco-mkml-models
mistralai-mistral-nemo-9330-v121-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
mistralai-mistral-nemo-9330-v121-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v121
mistralai-mistral-nemo-9330-v121-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v121/config.json
mistralai-mistral-nemo-9330-v121-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v121/special_tokens_map.json
mistralai-mistral-nemo-9330-v121-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v121/tokenizer_config.json
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: Downloaded to shared memory in 86.887s
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpd7yxdy7f, device:0
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: Saving flywheel model at /dev/shm/model_cache
mistralai-mistral-nemo-9330-v121-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/mistralai-mistral-nemo-9330-v121/flywheel_model.0.safetensors
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Job mistralai-mistral-nemo-9330-v121-mkmlizer completed after 123.34s with status: succeeded
Stopping job with name mistralai-mistral-nemo-9330-v121-mkmlizer
Pipeline stage MKMLizer completed in 123.68s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service mistralai-mistral-nemo-9330-v121
Waiting for inference service mistralai-mistral-nemo-9330-v121 to be ready
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: quantized model in 43.858s
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: Processed model ChaiML/0926-nemo-virgo-top-safe-bot-1edit in 130.745s
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: creating bucket guanaco-mkml-models
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-0926-nemo-virgo-t-3956-v7
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-0926-nemo-virgo-t-3956-v7/config.json
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-0926-nemo-virgo-t-3956-v7/special_tokens_map.json
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-0926-nemo-virgo-t-3956-v7/tokenizer_config.json
chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-0926-nemo-virgo-t-3956-v7/flywheel_model.0.safetensors
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Job chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer completed after 227.39s with status: succeeded
Stopping job with name chaiml-0926-nemo-virgo-t-3956-v7-mkmlizer
Pipeline stage MKMLizer completed in 227.73s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service chaiml-0926-nemo-virgo-t-3956-v7
Waiting for inference service chaiml-0926-nemo-virgo-t-3956-v7 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-v5-mkmlizer
Waiting for job on arushimgupta-peft-save-1-v5-mkmlizer to finish
arushimgupta-peft-save-1-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
arushimgupta-peft-save-1-v5-mkmlizer: ║     _____            __           __                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
arushimgupta-peft-save-1-v5-mkmlizer: ║       /___/                                                         ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Version: 0.11.12                                                   ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  https://mk1.ai                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  belonging to:                                                      ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Chai Research Corp.                                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
arushimgupta-peft-save-1-v5-mkmlizer: Downloaded to shared memory in 15.327s
arushimgupta-peft-save-1-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmph2e7k95s, device:0
arushimgupta-peft-save-1-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
arushimgupta-peft-save-1-v5-mkmlizer: 
Loading 0:   0%|          | 0/1203 [00:00<?, ?it/s]Traceback (most recent call last):
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
arushimgupta-peft-save-1-v5-mkmlizer:     cli()
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
arushimgupta-peft-save-1-v5-mkmlizer:     return self.main(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
arushimgupta-peft-save-1-v5-mkmlizer:     rv = self.invoke(ctx)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return __callback(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
arushimgupta-peft-save-1-v5-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
arushimgupta-peft-save-1-v5-mkmlizer:     flywheel.instrument(
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 93, in instrument
arushimgupta-peft-save-1-v5-mkmlizer:     compiler.save_pretrained(input_model_path, output_model_path, storage_format)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 23, in save_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     self.save_st_pretrained(input_model_path, output_model_path)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 38, in save_st_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in model_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/models/mistral.py", line 241, in tensor_merger
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in tensor_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py", line 217, in tensor_compiler
arushimgupta-peft-save-1-v5-mkmlizer:     compiled_tensor = runtime.instrument(tensor, profile.value)
arushimgupta-peft-save-1-v5-mkmlizer: RuntimeError: CUDA error: invalid configuration argument
arushimgupta-peft-save-1-v5-mkmlizer: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
arushimgupta-peft-save-1-v5-mkmlizer: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
arushimgupta-peft-save-1-v5-mkmlizer: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
arushimgupta-peft-save-1-v5-mkmlizer: Exception raised from c10_cuda_check_implementation at ../c10/cuda/CUDAException.cpp:43 (most recent call first):
arushimgupta-peft-save-1-v5-mkmlizer: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x71a4490cbf86 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x71a44907ad10 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, int, bool) + 0x118 (0x71a4491a6f08 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x71a3fbb0aa2e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x71a3fbb0b01b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #5: at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&) + 0x38c (0x71a3fbac9a0c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #6: at::native::copy_device_to_device(at::TensorIterator&, bool, bool) + 0xb25 (0x71a3fbaca715 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #7: <unknown function> + 0x1910312 (0x71a3fbacc312 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #8: <unknown function> + 0x1cbebff (0x71a431099bff in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #9: at::native::copy_(at::Tensor&, at::Tensor const&, bool) + 0x62 (0x71a43109b5a2 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #10: at::_ops::copy_::call(at::Tensor&, at::Tensor const&, bool) + 0x15c (0x71a431e5635c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x71a4313b96b1 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #12: <unknown function> + 0x2e19f8b (0x71a4321f4f8b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x71a4318fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #14: <unknown function> + 0x2c58a33 (0x71a432033a33 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x71a4318fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #16: <unknown function> + 0x470df1f (0x71a433ae8f1f in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #17: <unknown function> + 0x470e35e (0x71a433ae935e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x71a43198d68b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #19: at::native::to(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0xa2 (0x71a4313b6182 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #20: <unknown function> + 0x301e3b0 (0x71a4323f93b0 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #21: at::_ops::to_dtype::call(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0x178 (0x71a431b3d258 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #22: mkodec::instrument(at::Tensor, int) + 0x4b (0x71a36d9c81ab in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #23: <unknown function> + 0x981e2 (0x71a36d9b01e2 in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #24: <unknown function> + 0xa7b9b (0x71a36d9bfb9b in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #25: python3() [0x4fd907]
arushimgupta-peft-save-1-v5-mkmlizer: <omitting python frames>
arushimgupta-peft-save-1-v5-mkmlizer: frame #28: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #30: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #43: python3() [0x5095ce]
arushimgupta-peft-save-1-v5-mkmlizer: frame #50: python3() [0x509857]
arushimgupta-peft-save-1-v5-mkmlizer: frame #54: python3() [0x5cf913]
arushimgupta-peft-save-1-v5-mkmlizer: frame #57: python3() [0x5951c2]
arushimgupta-peft-save-1-v5-mkmlizer: frame #59: python3() [0x5c5ef7]
arushimgupta-peft-save-1-v5-mkmlizer: frame #60: python3() [0x5c1030]
arushimgupta-peft-save-1-v5-mkmlizer: frame #61: python3() [0x459781]
arushimgupta-peft-save-1-v5-mkmlizer: 
                                                   
arushimgupta-peft-save-1-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
arushimgupta-peft-save-1-v5-mkmlizer: ║     _____            __           __                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
arushimgupta-peft-save-1-v5-mkmlizer: ║       /___/                                                         ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Version: 0.11.12                                                   ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  https://mk1.ai                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  belonging to:                                                      ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Chai Research Corp.                                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Job arushimgupta-peft-save-1-v5-mkmlizer completed after 52.27s with status: failed
Stopping job with name arushimgupta-peft-save-1-v5-mkmlizer
%s, retrying in %s seconds...
Starting job with name arushimgupta-peft-save-1-v5-mkmlizer
Waiting for job on arushimgupta-peft-save-1-v5-mkmlizer to finish
arushimgupta-peft-save-1-v5-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
arushimgupta-peft-save-1-v5-mkmlizer: ║     _____            __           __                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
arushimgupta-peft-save-1-v5-mkmlizer: ║       /___/                                                         ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Version: 0.11.12                                                   ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  https://mk1.ai                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  The license key for the current software has been verified as      ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  belonging to:                                                      ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Chai Research Corp.                                                ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
arushimgupta-peft-save-1-v5-mkmlizer: ║  Expiration: 2024-10-15 23:59:59                                    ║
arushimgupta-peft-save-1-v5-mkmlizer: ║                                                                     ║
arushimgupta-peft-save-1-v5-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
arushimgupta-peft-save-1-v5-mkmlizer: Downloaded to shared memory in 16.231s
arushimgupta-peft-save-1-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpjwz23o0t, device:0
arushimgupta-peft-save-1-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
arushimgupta-peft-save-1-v5-mkmlizer: 
Loading 0:   0%|          | 0/1203 [00:00<?, ?it/s]Traceback (most recent call last):
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
arushimgupta-peft-save-1-v5-mkmlizer:     cli()
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
arushimgupta-peft-save-1-v5-mkmlizer:     return self.main(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
arushimgupta-peft-save-1-v5-mkmlizer:     rv = self.invoke(ctx)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return __callback(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
arushimgupta-peft-save-1-v5-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
arushimgupta-peft-save-1-v5-mkmlizer:     flywheel.instrument(
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 93, in instrument
arushimgupta-peft-save-1-v5-mkmlizer:     compiler.save_pretrained(input_model_path, output_model_path, storage_format)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 23, in save_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     self.save_st_pretrained(input_model_path, output_model_path)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 38, in save_st_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in model_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/models/mistral.py", line 241, in tensor_merger
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in tensor_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py", line 217, in tensor_compiler
arushimgupta-peft-save-1-v5-mkmlizer:     compiled_tensor = runtime.instrument(tensor, profile.value)
arushimgupta-peft-save-1-v5-mkmlizer: RuntimeError: CUDA error: invalid configuration argument
arushimgupta-peft-save-1-v5-mkmlizer: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
arushimgupta-peft-save-1-v5-mkmlizer: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
arushimgupta-peft-save-1-v5-mkmlizer: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
arushimgupta-peft-save-1-v5-mkmlizer: Exception raised from c10_cuda_check_implementation at ../c10/cuda/CUDAException.cpp:43 (most recent call first):
arushimgupta-peft-save-1-v5-mkmlizer: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x7e235e377f86 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x7e235e326d10 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, int, bool) + 0x118 (0x7e235e770f08 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x7e2310d0aa2e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x7e2310d0b01b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #5: at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&) + 0x38c (0x7e2310cc9a0c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #6: at::native::copy_device_to_device(at::TensorIterator&, bool, bool) + 0xb25 (0x7e2310cca715 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #7: <unknown function> + 0x1910312 (0x7e2310ccc312 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #8: <unknown function> + 0x1cbebff (0x7e2346299bff in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #9: at::native::copy_(at::Tensor&, at::Tensor const&, bool) + 0x62 (0x7e234629b5a2 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #10: at::_ops::copy_::call(at::Tensor&, at::Tensor const&, bool) + 0x15c (0x7e234705635c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x7e23465b96b1 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #12: <unknown function> + 0x2e19f8b (0x7e23473f4f8b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x7e2346afdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #14: <unknown function> + 0x2c58a33 (0x7e2347233a33 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x7e2346afdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #16: <unknown function> + 0x470df1f (0x7e2348ce8f1f in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #17: <unknown function> + 0x470e35e (0x7e2348ce935e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x7e2346b8d68b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #19: at::native::to(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0xa2 (0x7e23465b6182 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #20: <unknown function> + 0x301e3b0 (0x7e23475f93b0 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #21: at::_ops::to_dtype::call(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0x178 (0x7e2346d3d258 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #22: mkodec::instrument(at::Tensor, int) + 0x4b (0x7e2282bc81ab in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #23: <unknown function> + 0x981e2 (0x7e2282bb01e2 in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #24: <unknown function> + 0xa7b9b (0x7e2282bbfb9b in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #25: python3() [0x4fd907]
arushimgupta-peft-save-1-v5-mkmlizer: <omitting python frames>
arushimgupta-peft-save-1-v5-mkmlizer: frame #28: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #30: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #43: python3() [0x5095ce]
arushimgupta-peft-save-1-v5-mkmlizer: frame #50: python3() [0x509857]
arushimgupta-peft-save-1-v5-mkmlizer: frame #54: python3() [0x5cf913]
arushimgupta-peft-save-1-v5-mkmlizer: frame #57: python3() [0x5951c2]
arushimgupta-peft-save-1-v5-mkmlizer: frame #59: python3() [0x5c5ef7]
arushimgupta-peft-save-1-v5-mkmlizer: frame #60: python3() [0x5c1030]
arushimgupta-peft-save-1-v5-mkmlizer: frame #61: python3() [0x459781]
arushimgupta-peft-save-1-v5-mkmlizer: 
                                                   
arushimgupta-peft-save-1-v5-mkmlizer: 
Loading 0:   0%|          | 0/1203 [00:00<?, ?it/s]Traceback (most recent call last):
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
arushimgupta-peft-save-1-v5-mkmlizer:     cli()
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
arushimgupta-peft-save-1-v5-mkmlizer:     return self.main(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
arushimgupta-peft-save-1-v5-mkmlizer:     rv = self.invoke(ctx)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return __callback(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
arushimgupta-peft-save-1-v5-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
arushimgupta-peft-save-1-v5-mkmlizer:     flywheel.instrument(
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 93, in instrument
arushimgupta-peft-save-1-v5-mkmlizer:     compiler.save_pretrained(input_model_path, output_model_path, storage_format)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 23, in save_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     self.save_st_pretrained(input_model_path, output_model_path)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 38, in save_st_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in model_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/models/mistral.py", line 241, in tensor_merger
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in tensor_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py", line 217, in tensor_compiler
arushimgupta-peft-save-1-v5-mkmlizer:     compiled_tensor = runtime.instrument(tensor, profile.value)
arushimgupta-peft-save-1-v5-mkmlizer: RuntimeError: CUDA error: invalid configuration argument
arushimgupta-peft-save-1-v5-mkmlizer: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
arushimgupta-peft-save-1-v5-mkmlizer: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
arushimgupta-peft-save-1-v5-mkmlizer: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
arushimgupta-peft-save-1-v5-mkmlizer: Exception raised from c10_cuda_check_implementation at ../c10/cuda/CUDAException.cpp:43 (most recent call first):
arushimgupta-peft-save-1-v5-mkmlizer: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x797ea60cbf86 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x797ea607ad10 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, int, bool) + 0x118 (0x797ea61a6f08 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x797e58b0aa2e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x797e58b0b01b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #5: at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&) + 0x38c (0x797e58ac9a0c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #6: at::native::copy_device_to_device(at::TensorIterator&, bool, bool) + 0xb25 (0x797e58aca715 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #7: <unknown function> + 0x1910312 (0x797e58acc312 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #8: <unknown function> + 0x1cbebff (0x797e8e099bff in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #9: at::native::copy_(at::Tensor&, at::Tensor const&, bool) + 0x62 (0x797e8e09b5a2 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #10: at::_ops::copy_::call(at::Tensor&, at::Tensor const&, bool) + 0x15c (0x797e8ee5635c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x797e8e3b96b1 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #12: <unknown function> + 0x2e19f8b (0x797e8f1f4f8b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x797e8e8fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #14: <unknown function> + 0x2c58a33 (0x797e8f033a33 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x797e8e8fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #16: <unknown function> + 0x470df1f (0x797e90ae8f1f in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #17: <unknown function> + 0x470e35e (0x797e90ae935e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x797e8e98d68b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #19: at::native::to(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0xa2 (0x797e8e3b6182 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #20: <unknown function> + 0x301e3b0 (0x797e8f3f93b0 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #21: at::_ops::to_dtype::call(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0x178 (0x797e8eb3d258 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #22: mkodec::instrument(at::Tensor, int) + 0x4b (0x797dca9c81ab in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #23: <unknown function> + 0x981e2 (0x797dca9b01e2 in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #24: <unknown function> + 0xa7b9b (0x797dca9bfb9b in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #25: python3() [0x4fd907]
arushimgupta-peft-save-1-v5-mkmlizer: <omitting python frames>
arushimgupta-peft-save-1-v5-mkmlizer: frame #28: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #30: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #43: python3() [0x5095ce]
arushimgupta-peft-save-1-v5-mkmlizer: frame #50: python3() [0x509857]
arushimgupta-peft-save-1-v5-mkmlizer: frame #54: python3() [0x5cf913]
arushimgupta-peft-save-1-v5-mkmlizer: frame #57: python3() [0x5951c2]
arushimgupta-peft-save-1-v5-mkmlizer: frame #59: python3() [0x5c5ef7]
arushimgupta-peft-save-1-v5-mkmlizer: frame #60: python3() [0x5c1030]
arushimgupta-peft-save-1-v5-mkmlizer: frame #61: python3() [0x459781]
arushimgupta-peft-save-1-v5-mkmlizer: 
                                                   
Job arushimgupta-peft-save-1-v5-mkmlizer completed after 64.89s with status: failed
Stopping job with name arushimgupta-peft-save-1-v5-mkmlizer
%s, retrying in %s seconds...
Starting job with name arushimgupta-peft-save-1-v5-mkmlizer
Waiting for job on arushimgupta-peft-save-1-v5-mkmlizer to finish
arushimgupta-peft-save-1-v5-mkmlizer: Downloaded to shared memory in 16.662s
arushimgupta-peft-save-1-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpz0mzyzqk, device:0
arushimgupta-peft-save-1-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
arushimgupta-peft-save-1-v5-mkmlizer: Downloaded to shared memory in 15.827s
arushimgupta-peft-save-1-v5-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp9c4qp7od, device:0
arushimgupta-peft-save-1-v5-mkmlizer: Saving flywheel model at /dev/shm/model_cache
arushimgupta-peft-save-1-v5-mkmlizer: 
Loading 0:   0%|          | 0/1203 [00:00<?, ?it/s]Traceback (most recent call last):
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 151, in <module>
arushimgupta-peft-save-1-v5-mkmlizer:     cli()
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__
arushimgupta-peft-save-1-v5-mkmlizer:     return self.main(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main
arushimgupta-peft-save-1-v5-mkmlizer:     rv = self.invoke(ctx)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return _process_result(sub_ctx.command.invoke(sub_ctx))
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return ctx.invoke(self.callback, **ctx.params)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke
arushimgupta-peft-save-1-v5-mkmlizer:     return __callback(*args, **kwargs)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 42, in quantize
arushimgupta-peft-save-1-v5-mkmlizer:     quantize_model(temp_folder, output_path, profile, device)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/code/uploading/mkmlize.py", line 135, in quantize_model
Inference service mistralai-mistral-nemo-9330-v121 ready after 220.55023670196533s
arushimgupta-peft-save-1-v5-mkmlizer:     flywheel.instrument(
Pipeline stage MKMLDeployer completed in 221.10s
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/instrument.py", line 93, in instrument
run pipeline stage %s
arushimgupta-peft-save-1-v5-mkmlizer:     compiler.save_pretrained(input_model_path, output_model_path, storage_format)
Running pipeline stage StressChecker
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 23, in save_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     self.save_st_pretrained(input_model_path, output_model_path)
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/compiler.py", line 38, in save_st_pretrained
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in model_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/models/mistral.py", line 241, in tensor_merger
arushimgupta-peft-save-1-v5-mkmlizer:     for name, tensor in tensor_iterator:
arushimgupta-peft-save-1-v5-mkmlizer:   File "/opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py", line 217, in tensor_compiler
arushimgupta-peft-save-1-v5-mkmlizer:     compiled_tensor = runtime.instrument(tensor, profile.value)
arushimgupta-peft-save-1-v5-mkmlizer: RuntimeError: CUDA error: invalid configuration argument
arushimgupta-peft-save-1-v5-mkmlizer: CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
arushimgupta-peft-save-1-v5-mkmlizer: For debugging consider passing CUDA_LAUNCH_BLOCKING=1
arushimgupta-peft-save-1-v5-mkmlizer: Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
arushimgupta-peft-save-1-v5-mkmlizer: Exception raised from c10_cuda_check_implementation at ../c10/cuda/CUDAException.cpp:43 (most recent call first):
arushimgupta-peft-save-1-v5-mkmlizer: frame #0: c10::Error::Error(c10::SourceLocation, std::string) + 0x96 (0x751b9ef77f86 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #1: c10::detail::torchCheckFail(char const*, char const*, unsigned int, std::string const&) + 0x64 (0x751b9ef26d10 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10.so)
Received healthy response to inference request in 2.363326072692871s
arushimgupta-peft-save-1-v5-mkmlizer: frame #2: c10::cuda::c10_cuda_check_implementation(int, char const*, char const*, int, bool) + 0x118 (0x751b9f3a2f08 in /opt/conda/lib/python3.10/site-packages/torch/lib/libc10_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x751b5190aa2e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-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 (0x751b5190b01b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #5: at::native::direct_copy_kernel_cuda(at::TensorIteratorBase&) + 0x38c (0x751b518c9a0c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #6: at::native::copy_device_to_device(at::TensorIterator&, bool, bool) + 0xb25 (0x751b518ca715 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #7: <unknown function> + 0x1910312 (0x751b518cc312 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cuda.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #8: <unknown function> + 0x1cbebff (0x751b86e99bff in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #9: at::native::copy_(at::Tensor&, at::Tensor const&, bool) + 0x62 (0x751b86e9b5a2 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #10: at::_ops::copy_::call(at::Tensor&, at::Tensor const&, bool) + 0x15c (0x751b87c5635c in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x751b871b96b1 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #12: <unknown function> + 0x2e19f8b (0x751b87ff4f8b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
Received healthy response to inference request in 1.7707421779632568s
arushimgupta-peft-save-1-v5-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 (0x751b876fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #14: <unknown function> + 0x2c58a33 (0x751b87e33a33 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x751b876fdc25 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #16: <unknown function> + 0x470df1f (0x751b898e8f1f in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #17: <unknown function> + 0x470e35e (0x751b898e935e in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-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 (0x751b8778d68b in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #19: at::native::to(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0xa2 (0x751b871b6182 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #20: <unknown function> + 0x301e3b0 (0x751b881f93b0 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #21: at::_ops::to_dtype::call(at::Tensor const&, c10::ScalarType, bool, bool, std::optional<c10::MemoryFormat>) + 0x178 (0x751b8793d258 in /opt/conda/lib/python3.10/site-packages/torch/lib/libtorch_cpu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #22: mkodec::instrument(at::Tensor, int) + 0x4b (0x751ac37c81ab in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #23: <unknown function> + 0x981e2 (0x751ac37b01e2 in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
Received healthy response to inference request in 1.785046100616455s
arushimgupta-peft-save-1-v5-mkmlizer: frame #24: <unknown function> + 0xa7b9b (0x751ac37bfb9b in /opt/conda/lib/python3.10/site-packages/mk1/flywheel/runtime.cpython-310-x86_64-linux-gnu.so)
arushimgupta-peft-save-1-v5-mkmlizer: frame #25: python3() [0x4fd907]
arushimgupta-peft-save-1-v5-mkmlizer: <omitting python frames>
arushimgupta-peft-save-1-v5-mkmlizer: frame #28: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #30: python3() [0x5112cf]
arushimgupta-peft-save-1-v5-mkmlizer: frame #43: python3() [0x5095ce]
arushimgupta-peft-save-1-v5-mkmlizer: frame #50: python3() [0x509857]
arushimgupta-peft-save-1-v5-mkmlizer: frame #54: python3() [0x5cf913]
arushimgupta-peft-save-1-v5-mkmlizer: frame #57: python3() [0x5951c2]
arushimgupta-peft-save-1-v5-mkmlizer: frame #59: python3() [0x5c5ef7]
arushimgupta-peft-save-1-v5-mkmlizer: frame #60: python3() [0x5c1030]
Received healthy response to inference request in 1.944331169128418s
arushimgupta-peft-save-1-v5-mkmlizer: frame #61: python3() [0x459781]
arushimgupta-peft-save-1-v5-mkmlizer: 
                                                   
Received healthy response to inference request in 1.7631661891937256s
5 requests
0 failed requests
5th percentile: 1.7646813869476319
10th percentile: 1.7661965847015382
20th percentile: 1.7692269802093505
30th percentile: 1.7736029624938965
40th percentile: 1.7793245315551758
50th percentile: 1.785046100616455
60th percentile: 1.8487601280212402
70th percentile: 1.9124741554260254
80th percentile: 2.0281301498413087
90th percentile: 2.1957281112670897
95th percentile: 2.2795270919799804
99th percentile: 2.346566276550293
mean time: 1.9253223419189454
Pipeline stage StressChecker completed in 13.86s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
Job arushimgupta-peft-save-1-v5-mkmlizer completed after 54.6s with status: failed
Stopping job with name arushimgupta-peft-save-1-v5-mkmlizer
clean up pipeline due to error=MKMLizerError('')
Shutdown handler de-registered
MKMLizerError('')
arushimgupta-peft-save-1_v5 status is now failed due to DeploymentManager action
Pipeline stage TriggerMKMLProfilingPipeline completed in 8.56s
Shutdown handler de-registered
mistralai-mistral-nemo_9330_v121 status is now deployed due to DeploymentManager action
Inference service chaiml-0926-nemo-virgo-t-3956-v7 ready after 222.7054946422577s
Pipeline stage MKMLDeployer completed in 223.10s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 2.208041191101074s
Received healthy response to inference request in 1.8358640670776367s
Received healthy response to inference request in 1.628004789352417s
Received healthy response to inference request in 1.8195385932922363s
Received healthy response to inference request in 1.6778843402862549s
5 requests
0 failed requests
5th percentile: 1.6379806995391846
10th percentile: 1.6479566097259521
20th percentile: 1.6679084300994873
30th percentile: 1.7062151908874512
40th percentile: 1.7628768920898437
50th percentile: 1.8195385932922363
60th percentile: 1.8260687828063964
70th percentile: 1.8325989723205567
80th percentile: 1.9102994918823244
90th percentile: 2.0591703414916993
95th percentile: 2.1336057662963865
99th percentile: 2.1931541061401365
mean time: 1.8338665962219238
Pipeline stage StressChecker completed in 10.66s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 1.87s
Shutdown handler de-registered
chaiml-0926-nemo-virgo-t_3956_v7 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.31s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.22s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler
Waiting for inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler to be ready
Tearing down inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler
%s, retrying in %s seconds...
Creating inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler
Waiting for inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler to be ready
Tearing down inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler
%s, retrying in %s seconds...
Creating inference service chaiml-0926-nemo-virgo-t-3956-v7-profiler
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Tearing down inference service chaiml-0916-intent-suppo-6584-v5
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Pipeline stage MKMLDeleter completed in 36.42s
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Pipeline stage MKMLDeleter completed in 43.68s
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Pipeline stage MKMLModelDeleter completed in 179.55s
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Tearing down inference service blend-rofur-2024-10-03
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Pipeline stage MKMLDeleter completed in 42.17s
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Tearing down inference service blend-rofur-2024-10-03
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Creating inference service blend-rofur-2024-10-03
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Pipeline stage MKMLModelDeleter completed in 96.03s
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Pipeline stage MKMLModelDeleter completed in 33.75s
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