5 examples of 'torch repeat' in Python

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25def repeat(*args, **kwargs):
26 return torch.repeat(*args, **kwargs)
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4def repeat(tensor, K):
5 """
6 [B, ...] => [B*K, ...]
7
8 #-- Important --#
9 Used unsqueeze and transpose to avoid [K*B] when using torch.Tensor.repeat
10 """
11 if isinstance(tensor, torch.Tensor):
12 B, *size = tensor.size()
13 repeat_size = [1] + [K] + [1] * (tensor.dim() - 1)
14 tensor = tensor.unsqueeze(1).repeat(*repeat_size).view(B * K, *size)
15 return tensor
16 elif isinstance(tensor, list):
17 out = []
18 for x in tensor:
19 for _ in range(K):
20 out.append(x.copy())
21 return out
694@staticmethod
695def forward(ctx, input, repeats):
696 ctx.repeats = repeats
697 ctx.input_dims = input.dim()
698 return input.repeat(repeats)
822def repeat(self, *sizes):
823 """
824 Repeats :attr:`self` along the specified dimensions.
825
826 Unlike expand(), this function copies the tensor’s data.
827
828 Args:
829 sizes (torch.Size or int...): The number of times to repeat this tensor along each
830 dimension
831 """
832 raise NotImplementedError("repeat is not implemented")
1296def repeat(g, self, repeats):
1297 if not sym_help._is_value(repeats):
1298 repeats = g.op("Constant", value_t=torch.LongTensor(repeats))
1299 const_repeats = sym_help._maybe_get_const(repeats, 'is')
1300
1301 if self.isCompleteTensor() and not sym_help._is_value(const_repeats):
1302 sizes = self.type().sizes()
1303 diff_dims = len(const_repeats) - len(sizes)
1304 if diff_dims > 0:
1305 self = view(g, self, [1] * diff_dims + sizes)
1306 return g.op("Tile", self, repeats)

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