:这表示这是一个可选参数,例如clamp算子,可选参数python中可以用None,c++中用nullopt -func:clamp(Tensorself,Scalar?min=None,Scalar?max=None)->Tensordevice_check:NoCheck#TensorIteratorvariants:function,methodcpp_no_default_args:['min']structured_delegate:clamp.outdispatch:QuantizedCPU:clamp_quantized_cput...
Tensorother,*,Scalaralpha=1)->Tensordevice_check:NoCheck#TensorIteratorstructured_delegate:add.outvariants:function,methoddispatch:SparseCPU,SparseCUDA:add_sparseSparseCsrCPU,SparseCsrCUDA:add_sparse_csrMkldnnCPU:mkldnn_addZeroTensor:add_zerotensorNestedTensorCPU,NestedTensorCUDA:NestedTensor_add_Tensortags:ca...
CUDA: sub_out SparseCPU, SparseCUDA: sub_out_sparse # sub.Tensor 对应的虚函数表 - func: sub.Tensor(Tensor self, Tensor other, *, Scalar alpha=1) -> Tensor device_check: NoCheck # TensorIterator variants: function, method structured_delegate: sub.out dispatch: SparseCPU...
structured_delegate: addmm.out variants: function, method dispatch: MkldnnCPU: mkldnn_addmm_cpu SparseCPU: addmm_sparse_dense_cpu SparseCUDA: addmm_sparse_dense_cuda SparseCsrCPU, SparseCsrCUDA, SparseCsrMeta: addmm_sparse_compressed_dense242...
🐛 Describe the bug The operator is - func: aminmax(Tensor self, *, int? dim=None, bool keepdim=False) -> (Tensor min, Tensor max) device_check: NoCheck # TensorIterator structured_delegate: aminmax.out variants: function, method Look in ...
NoCheck# TensorIteratorstructured:Truestructured_inherits:TensorIteratorBasedispatch:CPU,CUDA:sub_outSparseCPU,SparseCUDA:sub_out_sparse# sub.Tensor 对应的虚函数表-func:sub.Tensor(Tensorself,Tensorother,*,Scalaralpha=1)->Tensordevice_check:NoCheck# TensorIteratorvariants:function,methodstructured_delegate:...
前面看到了如何在 GPU 上操作张量,我们接下来看看如何把模型放置到 GPU 之上。 首先我们定义了一个模型。 代码语言:javascript 复制 classToyModel(nn.Module):def__init__(self):super(ToyModel,self).__init__()self.net1=nn.Linear(10,10)self.relu=nn.ReLU()self.net2=nn.Linear(10,5)defforward(...
TFLite supports addingstructured metadatato the model. This includes: Model information- Overall description of the model as well as items such as license terms. SeeModelMetadata. Input information- Description of the inputs and pre-processing required such as normalization. ...
Structured # kernels are defined a little differently from normal kernels; in # particular, their shape checking logic is defined separately from # the kernel. Only out functions can be structured; other functions # delegate to the out function using the structured_delegate keyword....
'test/jit/xnnpack/test_xnnpack_delegate.py', 'test/jit_hooks/model.py', 'test/lazy/__init__.py', 'test/lazy/test_bindings.py', 'test/lazy/test_debug_util.py', 'test/lazy/test_extract_compiled_graph.py', 'test/lazy/test_meta_kernel.py', 'test/lazy/test_reuse_ir.py...