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Jan 19, 2022 · 📚 The doc issue The signature of Tensor.tile in the doc is wrong: Tensor.tile(*reps). But it should be Tensor.tile(dims) based on torch.tile(input, dims) Suggest a potential alternative/fix Tensor.tile(dims) cc @brianjo @mruberry

torch.tile¶ torch. tile (input, dims) → Tensor ¶ Constructs a tensor by repeating the elements of input.The dims argument specifies the number of repetitions in each dimension.. If dims specifies fewer dimensions than input has, then ones are prepended to dims until all dimensions are specified. For example, if input has shape (8, 6, 4, 2) and dims is (2, 2), then dims is treated as …

Feb 02, 2019 · An alternative way is to use torch.repeat(). So with torch.repeat() , you can specify the number of repeats for each dimension: >>> a = torch.randn(8, 3, 224, 224) >>> b = a.repeat(3, 1, 1, 1) >>> b.shape torch.Size([24, 3, 224, 224])

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torch.any. input ( Tensor) – the input tensor. Tests if any element in input evaluates to True. This function matches the behaviour of NumPy in returning output of dtype bool for all supported dtypes except uint8 . For uint8 the dtype of output is uint8 itself. For each row of input in the given dimension dim , returns True if any element in ...

I am trying to repeat a tensor in torch in two ways. For example repeating the tensor {1,2,3,4} 3 times both ways to yield; {1,2,3,4,1,2,3,4,1,2,3,4} {1,1,1,2,2,2,3,3,3,4,4,4} There is a built in torch:repeatTensor function which will generate the first of the two (like numpy.tile()) but I can't find one for the latter (like numpy.repeat()).I'm sure that I could call sort on the first to give ...

When this fire - brick lining is used only one end of the baffle tile need be provided with a shoulder , viz . ... ACETYLENE LAMPLIGHTING TORCH - 1,518 .

This operation creates a new tensor by replicating input multiples times. The output tensor's i'th dimension has input.dims(i) * multiples[i] ...

12.01.2018 · What is the equivalent way to do this in TensorFlow? I know unsqueeze() is equivalent to tf.expand_dims() but I don't TensorFlow has anything equivalent to expand(). I'm thinking of using tf.concat on a list of the 1 x 2 x 3 tensors but am …

While PyTorch follows Torch's naming convention and refers to ... from torchvision import datasets, transforms trans = transforms. ... x.tile(4,2).

An alternative way is to use torch.repeat() . ... But based on the answer from How to tile a tensor? we can do that so that the repeated ...

There is a built in torch:repeatTensor function which will generate the first of the two (like numpy.tile() ) but I can't find one for the ...

torch.any(input, dim, keepdim=False, *, out=None) → Tensor. For each row of input in the given dimension dim , returns True if any element in the row evaluate to True and False otherwise. If keepdim is True, the output tensor is of the same size as input except in …

22.01.2019 · loss = torch.stack(policy_losses).sum() + torch.stack(value_losses).sum() One is using torch.cat, the other uses torch.stack. As far as my understanding goes, the doc doesn't give any clear distinction between them. I would be happy to …

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02.02.2019 · An alternative way is to use torch.repeat (). So with torch.repeat (), you can specify the number of repeats for each dimension: >>> a = torch.randn (8, 3, 224, 224) >>> b = a.repeat (3, 1, 1, 1) >>> b.shape torch.Size ( [24, 3, 224, 224]) Sorry for the confusion. I omit to mention that the same element should be in succession.

20.02.2018 · A little function that builds on top of @Yang_Kai’s answer and provides an easy way to implement a tile function for 2D tensors: def torch_tile(tensor, dim, n): """Tile n times along the dim axis""" if dim == 0: return tensor.unsqueeze(0).transpose(0,1).repeat(1,n,1).view(-1,tensor.shape[1]) else: return tensor.unsqueeze(0).transpose(0,1 ...

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torch.tile(input, dims) → Tensor. Constructs a tensor by repeating the elements of input . The dims argument specifies the number of repetitions in each dimension. If dims specifies fewer dimensions than input has, then ones are prepended to dims until all dimensions are specified. For example, if input has shape (8, 6, 4, 2) and dims is (2 ...

19.01.2022 · 📚 The doc issue The signature of Tensor.tile in the doc is wrong: Tensor.tile(*reps). But it should be Tensor.tile(dims) based on torch.tile(input, dims) Suggest a potential alternative/fix Tensor.tile(dims) cc @brianjo @mruberry

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