svd(self, some=True, compute_uv=True) swapaxes(self, axis0, axis1) swapaxes_(self, axis0, axis1) swapdims(self, dim0, dim1) swapdims_(self, dim0, dim1) symeig(self, eigenvectors=False, upper=True) t(self) take(
repeat和expand tensor有两个成员函数来扩展某维的数据的尺寸:repeat和expand Tensor.repeat(*size):沿着特定的维度重复这个张量,和expand()不同的是,这个函数拷贝张量的数据。 Tensor.repeat(*sizes) → TensorRepeats this tensor along the specified dimensions.Unlike expand(), this function copies the tensor’...
使用PyTorch计算梯度数值 PyTorch的Autograd模块实现了深度学习的算法中的向传播求导数,在张量(Tensor类)上的所有操作,Autograd都能为他们自动提供微分,简化了手动计算导数的复杂过程。 在0.4以前的版本中,pytorch使用Variable类来自动计算所有的梯度,Variable类主要包含三个属性 data: 保存Variable所包含的Tensor grad: 保存...
5, 5, 2, 0, 1, 0, 1, 3, 2], [9, 6, 2, 8, 2, 1, 0, 1, 0, 2], [3, 7, 9, 1, 0, 2, 1.3, 2.3, 0, 1]]).astype(np.float32) print('==np.argmax(heatmap1d):', np.argmax(heatmap1d, axis=1)) heatmap1d = torch...
from torch import (randn,zeros,)from torch.nn import (Parameter,)tokens = vit.patch_embed(input)mask_token = Parameter(randn(token_dim))mask_tokens = mask_token.repeat(batch_size, n_tokens, 1)indices_to_mask = randn(batch_size, n_tokens)n_masked_tokens = int(0.5*n_tokens)indices_...
repeat(1, self.pred_len, 1) 这一句代码首先将大小为(batch_size, 96, 13)的x_enc沿着seq_len维度求平均,然后再repeat变成(batch_size, 24, 13),其中24表示pred_len,13表示96个时刻在13个变量上的平均值。 接着初始化大小为(batch_size, 24, 13)的全0矩阵zeros。 接着对x_enc进行分解得到两个趋势...
aten::fake_quantize_per_channel_affine(Tensor self, Tensor scale, Tensor zero_point, int axis, int quant_min, int quant_max) -> (Tensor)aten::fake_quantize_per_tensor_affine(Tensor self, float scale, int zero_point, int quant_min, int quant_max) -> (Tensor)...
repeat(batch_size, n_tokens, 1) indices_to_mask = randn(batch_size, n_tokens) n_masked_tokens = int(0.5*n_tokens) indices_to_mask = indices_to_mask.topk( k=n_masked_tokens, dim=1, ) indices_to_mask = indices_to_mask.indices bitmask = zeros(batch_size, n_tokens) bitmask = ...
Add support for reduction ops on multiple axis at a time (#91734) Add support for k greater than 16 for torch.topk (#94639) Build Add @pytorch in tools/bazel.bzl (#91424) Change visibility for //c10:headers (#91422) Simplify OpenMP detection in CMake (#91576) Use @pytorch// in ba...
,chunks为int,即需要分成的份数torch.gather(input,dim,index,out=None) →Tensor。Gathers values along an axis specified bydim.torch.index_select(input,dim,index,out=None) →Tensor,类似于标准库slice函数的 深度学习大概率用到的Pytorch内容基础 ...