is kept here for compatibility while the migration process is ongoing. Here you will learn the best coding tutorials on the latest technologies like a flutter, react js, python, Julia, and many more in a single place. No module named 'torch'. VS code does not even suggest the optimzier but the documentation clearly mention the optimizer. File "/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/op_builder/builder.py", line 118, in import_op What is a word for the arcane equivalent of a monastery? .PytorchPytorchtorchpythonFacebook GPU DNNTorch tensor TensorflowpytorchTo # image=Image.open("/home/chenyang/PycharmProjects/detect_traffic_sign/ni.jpg").convert('RGB') # t=transforms.Compose([ # transforms.Resize((416, 416)),]) image=t(image). But the input and output tensors are not named usually, hence you need to provide What am I doing wrong here in the PlotLegends specification? /usr/local/cuda/bin/nvcc -DTORCH_EXTENSION_NAME=fused_optim -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="gcc" -DPYBIND11_STDLIB="libstdcpp" -DPYBIND11_BUILD_ABI="cxxabi1011" -I/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/kernels/include -I/usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/TH -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS_ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 --use_fast_math -lineinfo -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -std=c++14 -c /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/multi_tensor_scale_kernel.cu -o multi_tensor_scale_kernel.cuda.o A ConvBn1d module is a module fused from Conv1d and BatchNorm1d, attached with FakeQuantize modules for weight, used in quantization aware training. However, the current operating path is /code/pytorch. Try to install PyTorch using pip: First create a Conda environment using: conda create -n env_pytorch python=3.6 Activate the environment using: conda activate Dynamic qconfig with weights quantized to torch.float16. I successfully installed pytorch via conda: I also successfully installed pytorch via pip: But, it only works in a jupyter notebook. But in the Pytorch s documents, there is torch.optim.lr_scheduler. You are using a very old PyTorch version. Given a Tensor quantized by linear(affine) quantization, returns the scale of the underlying quantizer(). This is the quantized version of LayerNorm. win10Pytorch 201941625Anaconda20195PytorchCondaHTTPError: HTTP 404 NOT FOUND for url >>import torch as tModule. operators. Quantization API Reference PyTorch 2.0 documentation Extending torch.func with autograd.Function, torch.Tensor (quantization related methods), Quantized dtypes and quantization schemes. Default qconfig configuration for per channel weight quantization. Can' t import torch.optim.lr_scheduler - PyTorch Forums in the Python console proved unfruitful - always giving me the same error. There's a documentation for torch.optim and its This module implements the quantized dynamic implementations of fused operations www.linuxfoundation.org/policies/. The nature of simulating nature: A Q&A with IBM Quantum researcher Dr. Jamie We've added a "Necessary cookies only" option to the cookie consent popup. raise CalledProcessError(retcode, process.args, This module contains Eager mode quantization APIs. Weboptim ="adamw_torch"TrainingArguments"adamw_hf" Huggingface TrainerTrainingArguments AttributeError: module 'torch.optim' has no attribute 'RMSProp' Web#optimizer = optim.AdamW (optimizer_grouped_parameters, lr=1e-5) ##torch.optim.AdamW (not working) step = 0 best_acc = 0 epoch = 10 writer = SummaryWriter(log_dir='model_best') for epoch in tqdm(range(epoch)): for idx, batch in tqdm(enumerate(train_loader), total=len(train_texts) // batch_size, leave=False): We and our partners use cookies to Store and/or access information on a device. here. Note: Even the most advanced machine translation cannot match the quality of professional translators. A limit involving the quotient of two sums. for inference. Crop1.transforms.RandomCrop2.transforms.CenterCrop3. transforms.RandomResizedCrop4.tr libtorchpytorch resnet50dimage = image.resize((224, 224),Image.ANT. Thus, I installed Pytorch for 3.6 again and the problem is solved. python-3.x 1613 Questions By clicking Sign up for GitHub, you agree to our terms of service and rev2023.3.3.43278. To learn more, see our tips on writing great answers. transformers - openi.pcl.ac.cn csv 235 Questions If I want to use torch.optim.lr_scheduler, how to set up the corresponding version of PyTorch? This is a sequential container which calls the Conv 3d and Batch Norm 3d modules. Quantization to work with this as well. Have a question about this project? Given a Tensor quantized by linear (affine) per-channel quantization, returns a tensor of zero_points of the underlying quantizer. RAdam PyTorch 1.13 documentation This module implements the quantizable versions of some of the nn layers. If you are adding a new entry/functionality, please, add it to the appropriate files under torch/ao/quantization/fx/, while adding an import statement here. subprocess.run( Config for specifying additional constraints for a given dtype, such as quantization value ranges, scale value ranges, and fixed quantization params, to be used in DTypeConfig. as follows: where clamp(.)\text{clamp}(.)clamp(.) pytorch pythonpython,import torchprint, 1.Tensor attributes2.tensor2.1 2.2 numpy2.3 tensor2.3.1 2.3.2 2.4 3.tensor3.1 3.1.1 Joining ops3.1.2 Clicing. time : 2023-03-02_17:15:31 Pytorch. Example usage::. keras 209 Questions What can a lawyer do if the client wants him to be acquitted of everything despite serious evidence? This module implements the quantized versions of the functional layers such as File "", line 1050, in _gcd_import To obtain better user experience, upgrade the browser to the latest version. Some functions of the website may be unavailable. quantization aware training. When the import torch command is executed, the torch folder is searched in the current directory by default. Quantized Tensors support a limited subset of data manipulation methods of the but when I follow the official verification I ge You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. Webtorch.optim optimizers have a different behavior if the gradient is 0 or None (in one case it does the step with a gradient of 0 and in the other it skips the step altogether). This is the quantized version of hardtanh(). A ConvBnReLU2d module is a module fused from Conv2d, BatchNorm2d and ReLU, attached with FakeQuantize modules for weight, used in quantization aware training. A ConvBn3d module is a module fused from Conv3d and BatchNorm3d, attached with FakeQuantize modules for weight, used in quantization aware training. Is Displayed During Distributed Model Training. dictionary 437 Questions What Do I Do If aicpu_kernels/libpt_kernels.so Does Not Exist? Returns a new tensor with the same data as the self tensor but of a different shape. A linear module attached with FakeQuantize modules for weight, used for quantization aware training. Default qconfig for quantizing weights only. dtypes, devices numpy4. Not the answer you're looking for? Is Displayed During Model Commissioning? Default fake_quant for per-channel weights. selenium 372 Questions Tensors5. This module implements versions of the key nn modules Conv2d() and the values observed during calibration (PTQ) or training (QAT). Simulate quantize and dequantize with fixed quantization parameters in training time. If you are using Anaconda Prompt , there is a simpler way to solve this. conda install -c pytorch pytorch Well occasionally send you account related emails. A quantized EmbeddingBag module with quantized packed weights as inputs. Instantly find the answers to all your questions about Huawei products and Web Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX. Applies 3D average-pooling operation in kDtimeskHkWkD \ times kH \times kWkDtimeskHkW regions by step size sDsHsWsD \times sH \times sWsDsHsW steps. Observer module for computing the quantization parameters based on the moving average of the min and max values. nvcc fatal : Unsupported gpu architecture 'compute_86' Find resources and get questions answered, A place to discuss PyTorch code, issues, install, research, Discover, publish, and reuse pre-trained models. Already on GitHub? Already on GitHub? Applies a linear transformation to the incoming quantized data: y=xAT+by = xA^T + by=xAT+b. What Do I Do If the Error Message "host not found." Applies 2D average-pooling operation in kHkWkH \times kWkHkW regions by step size sHsWsH \times sWsHsW steps. traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html. I think the connection between Pytorch and Python is not correctly changed. Do roots of these polynomials approach the negative of the Euler-Mascheroni constant? This is a sequential container which calls the Conv 2d and Batch Norm 2d modules. torch-0.4.0-cp35-cp35m-win_amd64.whl is not a supported wheel on this This site uses cookies. What Do I Do If the Error Message "ImportError: libhccl.so." AdamW,PyTorch previous kernel: registered at ../aten/src/ATen/functorch/BatchRulesScatterOps.cpp:1053 Describes how to quantize a layer or a part of the network by providing settings (observer classes) for activations and weights respectively. What Do I Do If the Error Message "Op type SigmoidCrossEntropyWithLogitsV2 of ops kernel AIcoreEngine is unsupported" Is Displayed? Mapping from model ops to torch.ao.quantization.QConfig s. Return the default QConfigMapping for post training quantization. FrameworkPTAdapter 2.0.1 PyTorch Network Model Porting and Training Guide 01. to your account, /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/library.py:130: UserWarning: Overriding a previously registered kernel for the same operator and the same dispatch key Converts a float tensor to a quantized tensor with given scale and zero point. Down/up samples the input to either the given size or the given scale_factor. import torch.optim as optim from sklearn.datasets import load_iris from sklearn.model_selection import train_test_split data = load_iris() X = data['data'] y = data['target'] X = torch.tensor(X, dtype=torch.float32) y = torch.tensor(y, dtype=torch.long) # split X_train, X_test, y_train, y_test = train_test_split(X, y, train_size=0.7, shuffle=True) Sign in Applies a 1D transposed convolution operator over an input image composed of several input planes. Modulenotfounderror: No module named torch ( Solved ) - Code File "/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/importlib/init.py", line 126, in import_module Fused version of default_per_channel_weight_fake_quant, with improved performance. Do quantization aware training and output a quantized model. Note that operator implementations currently only FAILED: multi_tensor_scale_kernel.cuda.o nvcc fatal : Unsupported gpu architecture 'compute_86' Not worked for me! opencv 219 Questions [4/7] /usr/local/cuda/bin/nvcc -DTORCH_EXTENSION_NAME=fused_optim -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="gcc" -DPYBIND11_STDLIB="libstdcpp" -DPYBIND11_BUILD_ABI="cxxabi1011" -I/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/kernels/include -I/usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/TH -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS_ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 --use_fast_math -lineinfo -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -std=c++14 -c /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/multi_tensor_adam.cu -o multi_tensor_adam.cuda.o Have a question about this project? Learn the simple implementation of PyTorch from scratch please see www.lfprojects.org/policies/. When import torch.optim.lr_scheduler in PyCharm, it shows that AttributeError: module torch.optim Quantize stub module, before calibration, this is same as an observer, it will be swapped as nnq.Quantize in convert. PyTorch_39_51CTO Applies a 2D convolution over a quantized 2D input composed of several input planes. This is a sequential container which calls the BatchNorm 2d and ReLU modules. Have a look at the website for the install instructions for the latest version. Observer module for computing the quantization parameters based on the running min and max values. . Check the install command line here[1]. Given a quantized Tensor, dequantize it and return the dequantized float Tensor. This is the quantized version of hardswish(). Note: This will install both torch and torchvision.. Now go to Python shell and import using the command: Have a question about this project? The above exception was the direct cause of the following exception: Root Cause (first observed failure): You may also want to check out all available functions/classes of the module torch.optim, or try the search function . Is Displayed When the Weight Is Loaded? Dynamic qconfig with weights quantized per channel. Dynamically quantized Linear, LSTM, i found my pip-package also doesnt have this line. subprocess.CalledProcessError: Command '['ninja', '-v']' returned non-zero exit status 1. Is this is the problem with respect to virtual environment? This module contains FX graph mode quantization APIs (prototype). Observer module for computing the quantization parameters based on the running per channel min and max values. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Leave your details and we'll be in touch. project, which has been established as PyTorch Project a Series of LF Projects, LLC. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. module = self._system_import(name, *args, **kwargs) File "C:\Users\Michael\PycharmProjects\Pytorch_2\venv\lib\site-packages\torch__init__.py", module = self._system_import(name, *args, **kwargs) ModuleNotFoundError: No module named 'torch._C'. Fused version of default_weight_fake_quant, with improved performance. If you are adding a new entry/functionality, please, add it to the WebPyTorch for former Torch users. , anacondatensorflowpytorchgym, Pytorch RuntimeErrorCUDA , spacy pyproject.toml , env env.render(), WARNING:tensorflow:Model (4, 112, 112, 3) ((None, 112), RuntimeErrormat1 mat2 25340 3601, stable_baselines module error -> gym.logger has no attribute MIN_LEVEL, PTpytorchpython, CNN CNN . I have installed Python. Default qconfig for quantizing activations only. Dynamic qconfig with weights quantized with a floating point zero_point. I think you see the doc for the master branch but use 0.12. I get the following error saying that torch doesn't have AdamW optimizer. Fuses a list of modules into a single module. function 162 Questions Simulate the quantize and dequantize operations in training time. When import torch.optim.lr_scheduler in PyCharm, it shows that AttributeError: module torch.optim has no attribute lr_scheduler. Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Asking for help, clarification, or responding to other answers. Is a collection of years plural or singular? What Do I Do If the Error Message "RuntimeError: ExchangeDevice:" Is Displayed During Model or Operator Running? Allowing ninja to set a default number of workers (overridable by setting the environment variable MAX_JOBS=N) Returns the state dict corresponding to the observer stats. Note that the choice of sss and zzz implies that zero is represented with no quantization error whenever zero is within string 299 Questions File "/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/op_builder/builder.py", line 135, in load Browse other questions tagged, Where developers & technologists share private knowledge with coworkers, Reach developers & technologists worldwide. Base fake quantize module Any fake quantize implementation should derive from this class. pytorch | AI A ConvReLU3d module is a fused module of Conv3d and ReLU, attached with FakeQuantize modules for weight for quantization aware training. Copyright 2023 Huawei Technologies Co., Ltd. All rights reserved. This is a sequential container which calls the Conv 1d, Batch Norm 1d, and ReLU modules. By continuing to browse the site you are agreeing to our use of cookies. web-scraping 300 Questions. By clicking Sign up for GitHub, you agree to our terms of service and This module implements the quantized versions of the nn layers such as It worked for numpy (sanity check, I suppose) but told me to go to Pytorch.org when I tried to install the "pytorch" or "torch" packages. Whenever I try to execute a script from the console, I get the error message: Note: This will install both torch and torchvision. I find my pip-package doesnt have this line. Example usage::. PyTorch1.1 1.2 PyTorch2.1 Numpy2.2 Variable2.3 Torch3.1 (1) (2) (3) 3.2 (1) (2) (3) 3.3 3.4 (1) (2) model.train()model.eval()Batch Normalization DropoutPyTorchmodeltrain/evaleval()BND PyTorchtorch.optim.lr_schedulerPyTorch, Autograd mechanics Manage Settings I installed on my macos by the official command : conda install pytorch torchvision -c pytorch Variable; Gradients; nn package. ModuleNotFoundError: No module named 'torch' (conda environment) amyxlu March 29, 2019, 4:04am #1. Is it possible to rotate a window 90 degrees if it has the same length and width? nvcc fatal : Unsupported gpu architecture 'compute_86' [6/7] c++ -MMD -MF colossal_C_frontend.o.d -DTORCH_EXTENSION_NAME=fused_optim -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="_gcc" -DPYBIND11_STDLIB="_libstdcpp" -DPYBIND11_BUILD_ABI="_cxxabi1011" -I/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/kernels/include -I/usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/TH -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -fPIC -std=c++14 -O3 -DVERSION_GE_1_1 -DVERSION_GE_1_3 -DVERSION_GE_1_5 -c /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/colossal_C_frontend.cpp -o colossal_C_frontend.o pyspark 157 Questions vegan) just to try it, does this inconvenience the caterers and staff? python - No module named "Torch" - Stack Overflow The module is mainly for debug and records the tensor values during runtime. _Eva_Hua-CSDN Config that defines the set of patterns that can be quantized on a given backend, and how reference quantized models can be produced from these patterns. regular full-precision tensor. pandas 2909 Questions Enable fake quantization for this module, if applicable. Fused version of default_qat_config, has performance benefits. So if you like to use the latest PyTorch, I think install from source is the only way. Copies the elements from src into self tensor and returns self. platform. in a backend. WebTo use torch.optim you have to construct an optimizer object, that will hold the current state and will update the parameters based on the computed gradients. for-loop 170 Questions The PyTorch Foundation is a project of The Linux Foundation. /usr/local/cuda/bin/nvcc -DTORCH_EXTENSION_NAME=fused_optim -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="gcc" -DPYBIND11_STDLIB="libstdcpp" -DPYBIND11_BUILD_ABI="cxxabi1011" -I/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/kernels/include -I/usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/TH -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS_ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 --use_fast_math -lineinfo -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -std=c++14 -c /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/multi_tensor_l2norm_kernel.cu -o multi_tensor_l2norm_kernel.cuda.o pytorch - No module named 'torch' or 'torch.C' - Stack Overflow Hi, which version of PyTorch do you use? Can' t import torch.optim.lr_scheduler. Usually if the torch/tensorflow has been successfully installed, you still cannot import those libraries, the reason is that the python environment This is a sequential container which calls the BatchNorm 3d and ReLU modules. Is Displayed During Model Commissioning. . [BUG]: run_gemini.sh RuntimeError: Error building extension 'fused_optim', https://pytorch.org/docs/stable/elastic/errors.html, torchrun --nproc_per_node 1 --master_port 19198 train_gemini_opt.py --mem_cap 0 --model_name_or_path facebook/opt-125m --batch_size 16, tee ./logs/colo_125m_bs_16_cap_0_gpu_1.log. 1.2 PyTorch with NumPy. FAILED: multi_tensor_l2norm_kernel.cuda.o like conv + relu. the custom operator mechanism. A dynamic quantized linear module with floating point tensor as inputs and outputs. how solve this problem?? My pytorch version is '1.9.1+cu102', python version is 3.7.11. If this is not a problem execute this program on both Jupiter and command line a Applies the quantized version of the threshold function element-wise: This is the quantized version of hardsigmoid(). WebHi, I am CodeTheBest. dispatch key: Meta [1/7] /usr/local/cuda/bin/nvcc -DTORCH_EXTENSION_NAME=fused_optim -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="gcc" -DPYBIND11_STDLIB="libstdcpp" -DPYBIND11_BUILD_ABI="cxxabi1011" -I/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/kernels/include -I/usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/TH -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS_ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 --use_fast_math -lineinfo -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -std=c++14 -c /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/multi_tensor_sgd_kernel.cu -o multi_tensor_sgd_kernel.cuda.o django-models 154 Questions VS code does not File "", line 1004, in _find_and_load_unlocked This is the quantized equivalent of Sigmoid. return importlib.import_module(self.prebuilt_import_path) ModuleNotFoundError: No module named 'colossalai._C.fused_optim'. bias. /usr/local/cuda/bin/nvcc -DTORCH_EXTENSION_NAME=fused_optim -DTORCH_API_INCLUDE_EXTENSION_H -DPYBIND11_COMPILER_TYPE="gcc" -DPYBIND11_STDLIB="libstdcpp" -DPYBIND11_BUILD_ABI="cxxabi1011" -I/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/kernels/include -I/usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/torch/csrc/api/include -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/TH -isystem /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/torch/include/THC -isystem /usr/local/cuda/include -isystem /workspace/nas-data/miniconda3/envs/gpt/include/python3.10 -D_GLIBCXX_USE_CXX11_ABI=0 -D__CUDA_NO_HALF_OPERATORS -D__CUDA_NO_HALF_CONVERSIONS_ -D__CUDA_NO_BFLOAT16_CONVERSIONS__ -D__CUDA_NO_HALF2_OPERATORS__ --expt-relaxed-constexpr -gencode=arch=compute_86,code=compute_86 -gencode=arch=compute_86,code=sm_86 --compiler-options '-fPIC' -O3 --use_fast_math -lineinfo -gencode arch=compute_60,code=sm_60 -gencode arch=compute_70,code=sm_70 -gencode arch=compute_75,code=sm_75 -gencode arch=compute_80,code=sm_80 -gencode arch=compute_86,code=sm_86 -std=c++14 -c /workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/site-packages/colossalai/kernel/cuda_native/csrc/multi_tensor_lamb.cu -o multi_tensor_lamb.cuda.o