1. 通过model.state_dict()输出模型结构,结构中key是权重名称,value是权重的值 2. 根据权重名称获取权重: fc_weight= model.state_dict()['fc_cls.weight']# 权重名称为:fc_cls.weight tensorflow 1. 首先要知道获取哪个tensor的权重: 打印tensor的名称 tvars = tf.get_col
在triton_config_with_settings,Inductor还会考虑grid能不能覆盖整个tensor。不过考虑到N卡上tl.program_id(0)最大到2147483647,这些调整基本都不会发生。 def pointwise( size_hints, triton_meta, tile_hint=None, filename=None, min_elem_per_thread=0, inductor_meta=None, ): ... #对于足够大的numel,bs...
bitwise_not_() → Tensor bmm(batch2) → Tensor bool() → Tensor byte() → Tensor cauchy_(median=0, sigma=1, *, generator=None) → Tensor ceil() → Tensor ceil_() → Tensor char() → Tensor cholesky(upper=False) → Tensor cholesky_inverse(upper=False) → Tensor cholesky_solve(inpu...
Returns a tensor of size size filled with fill_value. Parameters size (int...)– a list, tuple, or torch.Size of integers defining the shape of the output tensor. fill_value –the number to fill the output tensor with. out (Tensor, optional)– the output tensor. dtype (torch.dty...
add_image(tag, img_tensor, global_step=None, walltime=None, dataformats='CHW') 将图像数据添加到摘要中。 请注意,这需要pillow包。 参数: 1、tag (string) – 数据标识符 2、img_tensor (torch.Tensor, numpy.array, or string/blobname) – 图像数据 ...
1、tensor类型 torch.IntTensor() 接受三种参数 torch.IntTensor([[1,2,3],[4,5,6]]) #随机初始化 torch.IntTensor(np.arange(6).reshape(2,3)) torch.IntTensor(2,3).zero_() ①.zero_()尾巴的使用 常见用法 .add_(value) .abs_() .sin_() .cos_() .eq_(value) .floor() . x.dim...
placeholderrepresents a function input. Thenameattribute specifies the name this value will take on.targetis similarly the name of the argument.argsholds either: 1) nothing, or 2) a single argument denoting the default parameter of the function input.kwargsis don’t-care. Placeholders correspond...
[torch.Tensor]):print("my_compiler() called with FX graph:")gm.graph.print_tabular()returngm.forward# return a python callable@torchdynamo.optimize(my_compiler)deftrain_and_evaluate(model, criterion, optimizer, X_train, y_train, X...
torch.addcdiv(tensor, value=1, tensor1, tensor2, out=None):用tensor2对tensor1逐元素相除,然后乘以标量值value并加到tensor上。 torch.addcmul(tensor, value=1, tensor1, tensor2, out=None):用tensor2对tensor1逐元素相乘,并对结果乘以标量值value然后加到tensor,张量形状不需要匹配,但元素数量必须一致。
🐛 Describe the bug torch.compile returns wrong value for conditional mask tensor operation import torch torch.manual_seed(420) x = torch.randn(1, 3, 2, 2) class Model(torch.nn.Module): def forward(self, x): out = x mask1 = out > 0 out[ma...