as described in MinMaxObserver, specifically: where [xmin,xmax][x_\text{min}, x_\text{max}][xmin,xmax] denotes the range of the input data while By clicking or navigating, you agree to allow our usage of cookies. Can' t import torch.optim.lr_scheduler. This module implements the combined (fused) modules conv + relu which can What Do I Do If the Error Message "MemCopySync:drvMemcpy failed." File "/workspace/nas-data/miniconda3/envs/gpt/lib/python3.10/importlib/init.py", line 126, in import_module 1.2 PyTorch with NumPy. As the current maintainers of this site, Facebooks Cookies Policy applies. What Do I Do If the Error Message "match op inputs failed"Is Displayed When the Dynamic Shape Is Used? Applies a multi-layer gated recurrent unit (GRU) RNN to an input sequence. 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). Applies a 1D convolution over a quantized input signal composed of several quantized input planes. A ConvReLU2d module is a fused module of Conv2d and ReLU, attached with FakeQuantize modules for weight for quantization aware training. Note: This will install both torch and torchvision.. Now go to Python shell and import using the command: This is the quantized version of GroupNorm. Linear() which run in FP32 but with rounding applied to simulate the Fused version of default_qat_config, has performance benefits. Well occasionally send you account related emails. This file is in the process of migration to torch/ao/nn/quantized/dynamic, No relevant resource is found in the selected language. Note: This is the quantized version of Hardswish. What am I doing wrong here in the PlotLegends specification? What Do I Do If the Error Message "ImportError: libhccl.so." However, when I do that and then run "import torch" I received the following error: File "C:\Program Files\JetBrains\PyCharm Community Edition 2018.1.2\helpers\pydev_pydev_bundle\pydev_import_hook.py", line 19, in do_import. Some of our partners may process your data as a part of their legitimate business interest without asking for consent. Applies a 3D adaptive average pooling over a quantized input signal composed of several quantized input planes. Applies a 2D adaptive average pooling over a quantized input signal composed of several quantized input planes. Is Displayed During Model Running? Is Displayed During Distributed Model Training. An Elman RNN cell with tanh or ReLU non-linearity. You signed in with another tab or window. /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 model_parameters = model.named_parameters() for i in range(freeze): name, value = next(model_parameters) value.requires_grad = False weightrequires_gradFalse 5. # fliter Wrap the leaf child module in QuantWrapper if it has a valid qconfig Note that this function will modify the children of module inplace and it can return a new module which wraps the input module as well. . Not worked for me! scikit-learn 192 Questions appropriate file under the torch/ao/nn/quantized/dynamic, Calculating probabilities from d6 dice pool (Degenesis rules for botches and triggers). beautifulsoup 275 Questions Sign in Given a quantized Tensor, self.int_repr() returns a CPU Tensor with uint8_t as data type that stores the underlying uint8_t values of the given Tensor. What Do I Do If aicpu_kernels/libpt_kernels.so Does Not Exist? Upsamples the input to either the given size or the given scale_factor. Is it possible to create a concave light? Resizes self tensor to the specified size. I successfully installed pytorch via conda: I also successfully installed pytorch via pip: But, it only works in a jupyter notebook. Making statements based on opinion; back them up with references or personal experience. Default qconfig for quantizing activations only. This package is in the process of being deprecated. To view the purposes they believe they have legitimate interest for, or to object to this data processing use the vendor list link below. You are using a very old PyTorch version. project, which has been established as PyTorch Project a Series of LF Projects, LLC. Copyright 2005-2023 51CTO.COM ICP060544, ""ronghuaiyangPyTorchPyTorch. privacy statement. I get the following error saying that torch doesn't have AdamW optimizer. Where does this (supposedly) Gibson quote come from? What video game is Charlie playing in Poker Face S01E07? This is the quantized equivalent of LeakyReLU. Swaps the module if it has a quantized counterpart and it has an observer attached. AdamWBERToptim=adamw_torchTrainingArgumentsadamw_hf, optim ="adamw_torch"TrainingArguments"adamw_hf"Huggingface TrainerTrainingArguments, https://stackoverflow.com/questions/75535679/implementation-of-adamw-is-deprecated-and-will-be-removed-in-a-future-version-u, .net System.Runtime.InteropServices.=4.0.1.0, .NET WebApiAzure Application Insights, .net (NamedPipeClientStream)MessageModeC# UnauthorizedAccessException. 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. VS code does not even suggest the optimzier but the documentation clearly mention the optimizer. . thx, I am using the the pytorch_version 0.1.12 but getting the same error. What Do I Do If the MaxPoolGradWithArgmaxV1 and max Operators Report Errors During Model Commissioning? /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 registered at aten/src/ATen/RegisterSchema.cpp:6 during QAT. Supported types: torch.per_tensor_affine per tensor, asymmetric, torch.per_channel_affine per channel, asymmetric, torch.per_tensor_symmetric per tensor, symmetric, torch.per_channel_symmetric per channel, symmetric. dtypes, devices numpy4. The text was updated successfully, but these errors were encountered: You signed in with another tab or window. Check the install command line here[1]. What Do I Do If the Error Message "TVM/te/cce error." [0]: LSTMCell, GRUCell, and Allowing ninja to set a default number of workers (overridable by setting the environment variable MAX_JOBS=N) Caffe Layers backward forward Computational Graph , tensorflowpythontensorflow tensorflowtensorflow tensorflowpytorchpytorchtensorflow, tensorflowpythontensorflow tensorflowtensorflow tensorboardtrick1, import torchfrom torch import nnimport torch.nn.functional as Fclass dfcnn(n, opt=torch.optim.Adam(net.parameters(), lr=0.0008, betas=(0.9, 0.radients for next, https://zhuanlan.zhihu.com/p/67415439 https://www.jianshu.com/p/812fce7de08d. So if you like to use the latest PyTorch, I think install from source is the only way. I have installed Python. Copies the elements from src into self tensor and returns self. My pytorch version is '1.9.1+cu102', python version is 3.7.11. Note: Even the most advanced machine translation cannot match the quality of professional translators. This describes the quantization related functions of the torch namespace. The torch package installed in the system directory instead of the torch package in the current directory is called. json 281 Questions File "", line 1004, in _find_and_load_unlocked privacy statement. Currently only used by FX Graph Mode Quantization, but we may extend Eager Mode time : 2023-03-02_17:15:31 vegan) just to try it, does this inconvenience the caterers and staff? python-3.x 1613 Questions This is a sequential container which calls the BatchNorm 2d and ReLU modules. machine-learning 200 Questions A LinearReLU module fused from Linear and ReLU modules that can be used for dynamic quantization. How to react to a students panic attack in an oral exam? Read our privacy policy>. is the same as clamp() while the Sign up for a free GitHub account to open an issue and contact its maintainers and the community. Copyright 2023 Huawei Technologies Co., Ltd. All rights reserved. The text was updated successfully, but these errors were encountered: Hey, Already on GitHub? traceback : To enable traceback see: https://pytorch.org/docs/stable/elastic/errors.html. QAT Dynamic Modules. Have a look at the website for the install instructions for the latest version. operators. This is the quantized version of hardtanh(). nvcc fatal : Unsupported gpu architecture 'compute_86' in a backend. [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 Try to install PyTorch using pip: First create a Conda environment using: conda create -n env_pytorch python=3.6 torch.dtype Type to describe the data. This is a sequential container which calls the Conv1d and ReLU modules. The same message shows no matter if I try downloading the CUDA version or not, or if I choose to use the 3.5 or 3.6 Python link (I have Python 3.7). A quantized EmbeddingBag module with quantized packed weights as inputs. Learn more, including about available controls: Cookies Policy. Have a question about this project? A Conv3d module attached with FakeQuantize modules for weight, used for quantization aware training. Returns a new view of the self tensor with singleton dimensions expanded to a larger size. This module implements versions of the key nn modules Conv2d() and Applies a 1D transposed convolution operator over an input image composed of several input planes. One more thing is I am working in virtual environment. raise CalledProcessError(retcode, process.args, This module contains BackendConfig, a config object that defines how quantization is supported Manage Settings Well occasionally send you account related emails. then be quantized. Traceback (most recent call last): /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 This module contains FX graph mode quantization APIs (prototype). My pytorch version is '1.9.1+cu102', python version is 3.7.11. Quantize stub module, before calibration, this is same as an observer, it will be swapped as nnq.Quantize in convert. 1.1.1 Parameter()1.2 Containers()1.2.1 Module(1.2.2 Sequential()1.2.3 ModuleList1.2.4 ParameterList2.autograd,autograd windowscifar10_tutorial.py, BrokenPipeError: [Errno 32] Broken pipe When i :"run cifar10_tutorial.pyhttps://github.com/pytorch/examples/issues/201IPython, Pytorch0.41.Tensor Variable2. please see www.lfprojects.org/policies/. This is the quantized version of BatchNorm3d. By continuing to browse the site you are agreeing to our use of cookies. 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. But the input and output tensors are not named usually, hence you need to provide Given a quantized Tensor, dequantize it and return the dequantized float Tensor. can i just add this line to my init.py ? for-loop 170 Questions Using Kolmogorov complexity to measure difficulty of problems? WebpytorchModuleNotFoundError: No module named 'torch' pythonpytorchipython, jupyter notebookpytorch,>>>import torch as tModule anaconda pytorch jupyter python SpaceVision 2022-03-02 11:56:59 718 PyTorchNo A ConvReLU3d module is a fused module of Conv3d and ReLU, attached with FakeQuantize modules for weight for quantization aware training. module to replace FloatFunctional module before FX graph mode quantization, since activation_post_process will be inserted in top level module directly. I have not installed the CUDA toolkit. like conv + relu. Thanks for contributing an answer to Stack Overflow! Example usage::. Is Displayed When the Weight Is Loaded? Is this is the problem with respect to virtual environment? /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 I think the connection between Pytorch and Python is not correctly changed. I'll have to attempt this when I get home :), How Intuit democratizes AI development across teams through reusability. Applies the quantized version of the threshold function element-wise: This is the quantized version of hardsigmoid(). Applies a 1D convolution over a quantized 1D input composed of several input planes. Instantly find the answers to all your questions about Huawei products and The module records the running histogram of tensor values along with min/max values. Given a Tensor quantized by linear(affine) quantization, returns the zero_point of the underlying quantizer(). The torch package installed in the system directory instead of the torch package in the current directory is called. Observer module for computing the quantization parameters based on the moving average of the min and max values. WebPyTorch for former Torch users. Some functions of the website may be unavailable. What Do I Do If an Error Is Reported During CUDA Stream Synchronization? I find my pip-package doesnt have this line. A ConvBnReLU1d module is a module fused from Conv1d, BatchNorm1d and ReLU, attached with FakeQuantize modules for weight, used in quantization aware training. No BatchNorm variants as its usually folded into convolution Currently the latest version is 0.12 which you use. Dynamic qconfig with weights quantized per channel. Is Displayed During Model Commissioning. rev2023.3.3.43278. regex 259 Questions When the import torch command is executed, the torch folder is searched in the current directory by default. A limit involving the quotient of two sums. Applies a 2D max pooling over a quantized input signal composed of several quantized input planes. I have installed Pycharm. steps: install anaconda for windows 64bit for python 3.5 as per given link in the tensorflow install page but when I follow the official verification I ge Thus, I installed Pytorch for 3.6 again and the problem is solved. dispatch key: Meta Quantize the input float model with post training static quantization. www.linuxfoundation.org/policies/. FAILED: multi_tensor_lamb.cuda.o previous kernel: registered at ../aten/src/ATen/functorch/BatchRulesScatterOps.cpp:1053 A ConvBnReLU3d module is a module fused from Conv3d, BatchNorm3d and ReLU, attached with FakeQuantize modules for weight, used in quantization aware training. keras 209 Questions Is Displayed During Model Running? Is Displayed During Model Running? bias. Dequantize stub module, before calibration, this is same as identity, this will be swapped as nnq.DeQuantize in convert. Converts submodules in input module to a different module according to mapping by calling from_float method on the target module class. Autograd: VariableVariable TensorFunction 0.3 Join the PyTorch developer community to contribute, learn, and get your questions answered. opencv 219 Questions Check your local package, if necessary, add this line to initialize lr_scheduler. This is a sequential container which calls the Conv2d and ReLU modules. Next 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 Thank you! by providing the custom_module_config argument to both prepare and convert. A ConvBn3d module is a module fused from Conv3d and BatchNorm3d, attached with FakeQuantize modules for weight, used in quantization aware training. return _bootstrap._gcd_import(name[level:], package, level) Huawei uses machine translation combined with human proofreading to translate this document to different languages in order to help you better understand the content of this document. Describes how to quantize a layer or a part of the network by providing settings (observer classes) for activations and weights respectively. This is a sequential container which calls the Conv 2d, Batch Norm 2d, and ReLU modules. Default observer for a floating point zero-point. Is this a version issue or? datetime 198 Questions AdamW was added in PyTorch 1.2.0 so you need that version or higher. The torch.nn.quantized namespace is in the process of being deprecated. Is it possible to rotate a window 90 degrees if it has the same length and width? Quantization to work with this as well. An example of data being processed may be a unique identifier stored in a cookie. Given a Tensor quantized by linear(affine) quantization, returns the scale of the underlying quantizer(). This module implements the quantized versions of the functional layers such as 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 It worked for numpy (sanity check, I suppose) but told me Fuse modules like conv+bn, conv+bn+relu etc, model must be in eval mode. relu() supports quantized inputs. Ive double checked to ensure that the conda In Anaconda, I used the commands mentioned on Pytorch.org (06/05/18). [3/7] /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_l2norm_kernel.cu -o multi_tensor_l2norm_kernel.cuda.o
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