都是矩阵相乘,但是bmm的tensor必须是3D的,matmul没有强制规定 当操作的是3D tensor时,bmm与matmul等同 torch.matmul()是适用性最广的,能处理batch、广播的矩阵,推荐使用它 torch.matmul可以进行4维的tensor相乘, 甚至是5维 即只要前面几维值相同的,都可以忽略 总结: 二维矩阵乘法用,batch二维矩阵(即三维)用torch....
in <module> import deepspeed.ops.transformer.inference.triton.triton_matmul_kernel as triton_matmul_kernel File "/home/ray/anaconda3/lib/python3.9/site-packages/deepspeed/ops/transformer/inference/triton/triton_matmul_kernel.py", line 120, in <module> def _fp_matmul( File "/home/ray/anaconda3...
导入IREEPublicDialect并转传承内部使用的Dialect。 先看一下对于matmul这个例子来说,这个Pass起到的效果。 // ---// IR Dump Before IREEImportPublic (iree-import-public) //--- // #executable_target_cuda_nvptx_fb = #hal.executable.target<"cuda", "cuda-nvptx-fb", {target_arch = "sm_80"}...
Use GPU Coder with Deep Learning Toolbox to generate CUDA MEX or standalone CUDA code that runs on desktop or embedded targets. You can deploy generated standalone CUDA code that uses the CUDA deep neural network library (cuDNN), the TensorRT™ high performance inference library, or the ARM...
Use GPU Coder with Deep Learning Toolbox to generate CUDA MEX or standalone CUDA code that runs on desktop or embedded targets. You can deploy generated standalone CUDA code that uses the CUDA deep neural network library (cuDNN), the TensorRT™ high performance inference library, or the ARM...
I set up CUDA correctly and can compile CUDA code vianvcc. I do have multiple CUDA versions on my machine. Additional context Can you show me the installation log of the installation? pip uninstall torch-scatter pip install --verbose torch-scatter -f https://pytorch-geometric.com/whl/torch...
inp = torch.randn(8, 3, 224, 224, device='cuda') mod = models.resnet18().cuda() flop_counter = FlopCounterMode(mod) with flop_counter: mod(inp).sum().backward() with flop_counter: mod(inp).sum().backward() exit(0) from torch.fx.experimental.symbolic_shapes import ShapeEnv ...
example net= importNetworkFromONNX(modelfile,Name=Value)imports a pretrained ONNX network with additional options specified by one or more name-value arguments. For example,Namespace="CustomLayers"saves any generated custom layers and associated functions in the+CustomLayersnamespace in the current ...
You can deploy generated standalone CUDA code that uses the CUDA deep neural network library (cuDNN), the TensorRT™ high performance inference library, or the ARM Compute library for Mali GPU. For more information, see Deep Learning with GPU Coder (GPU Coder). importONNXNetwork returns the...
MatMul fullyConnectedLayer if ONNX network is recurrent, otherwise convolution2dLayer MaxPool maxPooling1dLayer or maxPooling2dLayer Mul multiplicationLayer Relu reluLayer or clippedReluLayer PRelu preluLayer Sigmoid sigmoidLayer Softmax softmaxLayer Sum additionLayer Tanh tanhLayer * If importONNXLayers...