Creation operations tensor() sparse_coo_tensor() as_tensor() as_strided() from_numpy() zeros() zeros_like() ones() ones_like() arange() range() linspace() logspace() eye() empty() empty_like() empty_strided() full() full_like() quantize_per_tensor() quantize_per_channel() dequ...
index (LongTensor)– the indices of elements to scatter, can be either empty or of the same dimensionality as src. When empty, the operation returns self unchanged. src (Tensor or float)– the source element(s) to scatter. 要填进去的元素 reduce (str, optional)– reduction operation to ap...
scatter_ 按照 index 将 source 中的值填充到 target 中。 import torch # 创建一个 3x3 的张量 src = torch.tensor([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) # 创建一个 2x3 的索引张量 index = torch.tensor([[0, 2, 1], [1, 0, 2]]) # 创建一个空的 2x3 的目标张量 target ...
scatter(dim, index, source) → Tensor scatter_(dim, index, src) → Tensor scatter_add_(dim, index, other) → Tensor scatter_add(dim, index, source) → Tensor select(dim, index) → Tensor set_(source=None, storage_offset=0, size=None, stride=None) → Tensor share_memory_()[source]...
The source should have at least as many elements as the number of ones in mask Parameters mask (BoolTensor)– the boolean mask source (Tensor)– the tensor to copy from Note The mask operates on the self tensor, not on the given source tensor. masked_scatter(mask, tensor)→ Tensor ...
torch.as_strided 是 支持fp32 torch.from_numpy 是 支持输出fp16,fp32,fp64,uint8,int8,int16,int32,int64,bool torch.frombuffer 是 支持bf16,fp16,fp32,fp64,uint8,int8,int16,int32,int64,bool torch.zeros 是 torch.zeros_like 是 支持bf16,fp16,fp32,uint8,int8,int16,int...
Add decomp/lowering: aten.as_strided_scatter#93650 aten.grid_sampler_2d_backward (higher priority) aten.upsample_bilinear2d_backward (higher priority) aten._adaptive_avg_pool2d_backward aten.upsample_bicubic2d_backward aten._fused_moving_avg_obs_fq_helper ...
emit("aten::as_strided_scatter : (Tensor, Tensor, int[], int[], int?) -> (Tensor)") emit("aten::upsample_nearest2d : (Tensor, int[], float?, float?) -> (Tensor)") emit("aten::scaled_dot_product_attention : (Tensor, Tensor, Tensor, Tensor?, float, bool, float?) -> (Te...
torch.Tensor.as_strided Supported 39 torch.Tensor.atan Supported 40 torch.Tensor.atan2 Supported 41 torch.Tensor.atan2_ Supported 42 torch.Tensor.atan_ Supported 43 torch.Tensor.baddbmm Supported 44 torch.Tensor.baddbmm_ Supported 45 torch.Tensor.bernoulli ...
import numpy as np flag = True if flag: arr = np.ones((3,3)) print('ndarray的数据类型:',arr.dtype) # t = torch.tensor(arr,device = 'cuda') t = torch.tensor(arr) print(t) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10.