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WR2 | __add__ (self, float arg0) |
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WR2 | __add__ (self, Scalar arg0) |
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WR2 | __add__ (self, WR2 arg0) |
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Scalar | __call__ (self, int arg0, int arg1) |
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Scalar | __call__ (self, int arg0, int arg1) |
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None | __init__ (self) |
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None | __init__ (self, torch.Tensor arg0, int arg1) |
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None | __init__ (self, WR2 arg0) |
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None | __init__ (self, torch.Tensor arg0) |
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None | __init__ (self, R2 arg0) |
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WR2 | __mul__ (self, float arg0) |
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WR2 | __mul__ (self, Scalar arg0) |
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WR2 | __neg__ (self) |
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WR2 | __pow__ (self, float arg0) |
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WR2 | __pow__ (self, Scalar arg0) |
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WR2 | __radd__ (self, float arg0) |
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str | __repr__ (self) |
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WR2 | __rmul__ (self, float arg0) |
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Tensor | __rpow__ (self, float arg0) |
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WR2 | __rsub__ (self, float arg0) |
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WR2 | __rtruediv__ (self, float arg0) |
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str | __str__ (self) |
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WR2 | __sub__ (self, float arg0) |
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WR2 | __sub__ (self, Scalar arg0) |
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WR2 | __sub__ (self, WR2 arg0) |
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WR2 | __truediv__ (self, float arg0) |
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WR2 | __truediv__ (self, Scalar arg0) |
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WR2 | __truediv__ (self, WR2 arg0) |
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bool | batched (self) |
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WR2 | clone (self) |
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torch.Tensor | copy_ (self, torch.Tensor arg0, bool arg1) |
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WR2 | cross (self, Vec arg0) |
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WR2 | cross (self, Rot arg0) |
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WR2 | cross (self, WR2 arg0) |
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bool | defined (self) |
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WR2 | detach (self) |
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torch.Tensor | detach_ (self) |
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R2 | dexp (self) |
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int | dim (self) |
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Scalar | dot (self, Vec arg0) |
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Scalar | dot (self, Rot arg0) |
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Scalar | dot (self, WR2 arg0) |
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R2 | drotate (self, Rot arg0) |
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Rot | exp (self) |
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Scalar | norm (self) |
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Scalar | norm_sq (self) |
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R2 | outer (self, Vec arg0) |
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R2 | outer (self, Rot arg0) |
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R2 | outer (self, WR2 arg0) |
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torch.Tensor | requires_grad_ (self, bool arg0) |
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WR2 | rotate (self, Rot arg0) |
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Tensor | tensor (self) |
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WR2 | to (self, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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torch.Tensor | torch (self) |
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torch.Tensor | torch (self) |
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torch.Tensor | zero_ (self) |
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WR2BaseView | base (self) |
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WR2BatchView | batch (self) |
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torch.device | device (self) |
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torch.dtype | dtype (self) |
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torch.Tensor | grad (self) |
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bool | requires_grad (self) |
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tuple[int,...] | shape (self) |
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WR2 | empty (*torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | empty (tuple[int,...] batch_shape, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | empty_like (WR2 arg0) |
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WR2 | fill (float x, float y, float z, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | fill (Scalar x, Scalar y, Scalar z) |
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WR2 | full (float fill_value, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | full (tuple[int,...] batch_shape, float fill_value, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | full_like (WR2 arg0, float arg1) |
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R2 | identity_map (*torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | linspace (WR2 start, WR2 end, int nstep, int dim=0) |
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WR2 | logspace (WR2 start, WR2 end, int nstep, int dim=0, float base=10.0) |
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WR2 | ones (*torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | ones (tuple[int,...] batch_shape, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | ones_like (WR2 arg0) |
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WR2 | zeros (*torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | zeros (tuple[int,...] batch_shape, *torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) |
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WR2 | zeros_like (WR2 arg0) |
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