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@ -335,10 +335,7 @@ class SpatialSoftmax(nn.Module):
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# we could use torch.linspace directly but that seems to behave slightly differently than numpy
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# we could use torch.linspace directly but that seems to behave slightly differently than numpy
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# and cause a small degradation in pc_success of pre-trained models.
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# and cause a small degradation in pc_success of pre-trained models.
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pos_x, pos_y = np.meshgrid(
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pos_x, pos_y = np.meshgrid(np.linspace(-1.0, 1.0, self._in_w), np.linspace(-1.0, 1.0, self._in_h))
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np.linspace(-1., 1., self._in_w),
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np.linspace(-1., 1., self._in_h)
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)
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pos_x = torch.from_numpy(pos_x.reshape(self._in_h * self._in_w, 1)).float()
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pos_x = torch.from_numpy(pos_x.reshape(self._in_h * self._in_w, 1)).float()
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pos_y = torch.from_numpy(pos_y.reshape(self._in_h * self._in_w, 1)).float()
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pos_y = torch.from_numpy(pos_y.reshape(self._in_h * self._in_w, 1)).float()
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# register as buffer so it's moved to the correct device, etc.
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# register as buffer so it's moved to the correct device, etc.
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