Torch.Indef.Static.NN.Sampling

1d sampling

_temporalUpSamplingNearest_updateOutput :: Tensor d -> Tensor d -> Int -> IO ()

temporalUpSamplingNearest forward pass (updates the output tensor)

_temporalUpSamplingNearest_updateGradInput :: Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

temporalUpSamplingNearest backward-update (updates the layer and bias tensors)

_temporalUpSamplingLinear_updateOutput :: Tensor d -> Tensor d -> Int -> IO ()

temporalUpSamplingLinear forward pass (updates the output tensor)

_temporalUpSamplingLinear_updateGradInput :: Tensor d -> Tensor d -> Int -> Int -> Int -> Int -> IO ()

temporalUpSamplingLinear backward-update (updates the layer and bias tensors)

2d sampling

_spatialSubSampling_updateOutput :: Tensor d -> Tensor d -> Tensor d -> Tensor d -> Int -> Int -> Int -> Int -> IO ()

spatialSubSampling forward pass (updates the output tensor)

_spatialSubSampling_updateGradInput :: Tensor d -> Tensor d -> Tensor d -> Tensor d -> Int -> Int -> Int -> Int -> IO ()

spatialSubSampling backward-update (updates the layer and bias tensors)

_spatialSubSampling_accGradParameters :: Tensor d -> Tensor d -> Tensor d -> Tensor d -> Int -> Int -> Int -> Int -> Double -> IO ()

spatialSubSampling backward-update (updates the layer and bias tensors). Called accGradParameters in C to indicate accumulating the gradient parameters.

_spatialUpSamplingNearest_updateOutput :: Tensor d -> Tensor d -> Int -> IO ()

spatialUpSamplingNearest forward pass (updates the output tensor)

_spatialUpSamplingNearest_updateGradInput :: Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

spatialUpSamplingNearest backward-update (updates the layer and bias tensors)

_spatialUpSamplingBilinear_updateOutput :: Tensor d -> Tensor d -> Int -> Int -> IO ()

spatialUpSamplingBilinear forward pass (updates the output tensor)

_spatialUpSamplingBilinear_updateGradInput :: Tensor d -> Tensor d -> Int -> Int -> Int -> Int -> Int -> Int -> IO ()

spatialUpSamplingBilinear backward-update (updates the layer and bias tensors)

_spatialGridSamplerBilinear_updateOutput :: Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

spatialGridSamplerBilinear forward pass (updates the output tensor)

_spatialGridSamplerBilinear_updateGradInput :: Tensor d -> Tensor d -> Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

spatialGridSamplerBilinear backward-update (updates the layer and bias tensors)

3d sampling

_volumetricGridSamplerBilinear_updateOutput :: Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

volumetricGridSamplerBilinear forward pass (updates the output tensor)

_volumetricGridSamplerBilinear_updateGradInput :: Tensor d -> Tensor d -> Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

volumetricGridSamplerBilinear backward-update (updates the layer and bias tensors)

_volumetricUpSamplingNearest_updateOutput :: Tensor d -> Tensor d -> Int -> IO ()

volumetricUpSamplingNearest forward pass (updates the output tensor)

_volumetricUpSamplingNearest_updateGradInput :: Tensor d -> Tensor d -> Tensor d -> Int -> IO ()

volumetricUpSamplingNearest backward-update (updates the layer and bias tensors)

_volumetricUpSamplingTrilinear_updateOutput :: Tensor d -> Tensor d -> Int -> Int -> Int -> IO ()

volumetricUpSamplingTrilinear forward pass (updates the output tensor)

_volumetricUpSamplingTrilinear_updateGradInput :: Tensor d -> Tensor d -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> Int -> IO ()

volumetricUpSamplingTrilinear backward-update (updates the layer and bias tensors)