🎨 Format Python code with psf/black (#333)
Co-authored-by: ndem0 <ndem0@users.noreply.github.com>
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@@ -57,14 +57,12 @@ class OrthogonalBlock(torch.nn.Module):
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v = torch.select(X, self.dim, i).clone()
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for j in range(i):
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vj = torch.select(result, self.dim, j).clone()
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v = v - torch.sum(v * vj,
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dim=self.dim, keepdim=True) * vj
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v = v - torch.sum(v * vj, dim=self.dim, keepdim=True) * vj
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# result_i = torch.select(result, self.dim, i)
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result_i = v / torch.linalg.norm(v)
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result = self._differentiable_copy(result, i, result_i)
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return result
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def _differentiable_copy(self, result, idx, value):
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"""
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Perform a differentiable copy operation on a tensor.
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@@ -104,8 +102,10 @@ class OrthogonalBlock(torch.nn.Module):
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# check consistency
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check_consistency(value, int)
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if value not in [0, 1, -1]:
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raise IndexError('Dimension out of range (expected to be in '
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f'range of [-1, 1], but got {value})')
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raise IndexError(
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"Dimension out of range (expected to be in "
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f"range of [-1, 1], but got {value})"
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)
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# assign value
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self._dim = value
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