tensors:这个参数可能是一个包含多个张量(或数组)的列表或元组,这些张量将用于生成网格点坐标。 **kwargs:这是一个关键字参数列表,允许传递额外的参数给_vf.meshgrid函数。这些参数可能用于控制网格的生成方式,如索引顺序、稀疏性等。 解释# type: ignore[attr-defined]注释: 这条注释是用于类型检查时的忽略指令...
Hi @hameerabbasi, This is a small tweak to make sure nonzero returns Tensor's instead of NumPy arrays.
/home/ljx/.local/lib/python3.6/site-packages/torch/functional.py:445: UserWarning: torch.meshgrid: in an upcoming release, it will be required to pass the indexing argument. (Triggered internally at /media/nvidia/NVME/p…
return_offsets_mapping, **kwargs) 1926 stack = tf.stack(stack, axis=0) 1927 elif return_tensors == "pt": -> 1928 stack = torch.stack(stack, dim=0) 1929 elif not return_tensors and len(stack) == 1: 1930 stack = stack[0] TypeError: expected Tensor as element 0 in argument 0...
🚀 Feature I am working on medical image analysis, in which for data sample (i.e. medial image) it contains multiple samples (data + label) for training. How can I write my own dataset and dataloader to extract all the tensors from one im...
def forward(self, inputs) -> Tuple[torch.Tensor, torch.Tensor]: x0: torch.Tensor = self.conv_branch_0(inputs) x1: torch.Tensor = self.conv_branch_1(inputs) x1 = x1.mean(dim=(-1, -2)) return x0, x1 def convert(model: torch.nn.Module, example: Optional[torch.Tensor] = Non...
"""Unwrap resource variable/ndarray to return tensors.""" if resource_variable_ops.is_resource_variable(x): return x.handle if isinstance(x, np_arrays.ndarray): return x.data return x @@ -1034,7 +1029,6 @@ def gradient(self, " of Tensors or Variables to be differentiated," " but...
FixTensorIterator::is_scalarfor empty np-tensors… bfde834 tringwaldmentioned this issueDec 4, 2023 This was referencedDec 5, 2023 Segmentation fault when multiplying *float16 tensor with int tensor and one shape is: (0,0).#115066
🐛 Describe the bug Layer normalization on NestedTensor returns the result of layer normalization, mean, and standard deviation. It should return 3 NTs if not reducing on the ragged dimension, and 3 dense tensors otherwise. e.g. import to...
I try to use "image.decode_image" to read image file as tensor, but this function returns a tensor without "shape". As said in the doc: Their input and output are all of variable size. If you need fixed size images, pass the output of the decode Ops to one of the cropping and ...