(atten_masks).to(torch.float16).bool().npu() if sparse_params[0] == 2 or sparse_params[0] == 3 or sparse_params[0] == 4: atten_masks = torch.from_numpy(np.triu(np.ones([2048, 2048]), k=1)) atten_mask = torch.tensor(atten_masks).to(torch.float16).bool().npu() ...
Modifications to the tensor will be reflected in the ndarray and vice versa. The returned tensor is not resizable. It currently accepts ndarray with dtypes of numpy.float64, numpy.float32, numpy.float16, numpy.int64, numpy.int32, numpy.int16, numpy.int8, numpy.uint8, and numpy.bool. ...
a_float32 = torch.rand((8, 8), device="cuda") b_float32 = torch.rand((8, 8), device="cuda") c_float32 = torch.rand((8, 8), device="cuda") d_float32 = torch.rand((8, 8), device="cuda")with autocast(): e_float16 = (a_float32, b_float32) with autocast(enabled=...
🐛 Describe the bug import torch inp = torch.randn(8, 4096, device=torch.cuda.current_device(), requires_grad=True) bf16_inp = inp.detach().clone().to(torch.bfloat16).requires_grad_(True) indice = torch.randint(0, 8, (8192,)).view(-1, 1)...
bfloat16 bilinear binary_cross_entropy_with_logits bincount binomial bitwise_and bitwise_not bitwise_or bitwise_xor blackman_window block_diag bmm bool broadcast_shapes broadcast_tensors broadcast_to bucketize can_cast cartesian_prod cat cdist cdouble ceil ceil_ celu celu_ cfloat chain_matmul ...
🐛 Describe the bug torch.linalg.matmul and torch.Tensor.matmul with torch.bfloat16 can still run without mkldnn and return incorrect results, even in PyTorch 1.13.1 (the latest released docker environment) This unexpected behavior is rel...
2个规则弄懂numpy的broadcast广播机制 - 知乎 (zhihu.com) 举个例子: A = np.zeros((2,5,3,4)) B = np.zeros((3,4)) print((A+B).shape) # 输出 (2, 5, 3, 4) A = np.zeros((4)) B = np.zeros((3,4)) print((A+B).shape) # 输出(3,4) ...
不支持操作类型扩展:Torch Tensor只支持固定的数据类型,如float32、int64等,不像python原生的List或Numpy数组那样可以存储多种不同的数据类型。 不直接支持GPU加速:Torch Tensor默认在CPU上运行,如果想要利用GPU进行加速,需要将Tensor数据移动到GPU上进行运算。这需要手动管理Tensor的设备位置,增加了编码和维护的复杂性。
torch.hub._validate_not_a_forked_repo=lambdaa,b,c:True#加载带权重ResNet模型resnet50_model = torch.hub.load('pytorch/vision:v0.10.0','resnet50', weights=True) resnet50_model.eval() importnumpyasnpimporttimeimporttorch.backends.cudnnascudnn ...
numpy 数组对象是 NumPy 中最核心的组成部分,这个数组叫做 ndarray,是“N-dimensional array”的缩写。其中的 N 是一个数字,指代维度. 在 NumPy 中,数组是由 numpy.ndarray 类来实现的,它是 NumPy 的核心数据结构。 而Python 中的列表,其实也可以达到与 NumPy 数组相同的功能,但它们又有差异,做个对比你就能体...