parameters: (self, grad_masks)
return_statement: return self.vertices.grad.get()
docstring: Compute gradient of vertices given mask gradients.
          Args:
              grad_masks: B X 256 X 256 numpy array
          Returns:
              grad_vertices: B X N X 3 numpy array
docstring_summary: Compute gradient of vertices given mask gradients.
          Args:
              grad_masks: B X 256 X 256 numpy array
          Returns:
              grad_vertices: B X N X 3 numpy array
docstring_tokens: Compute gradient of vertices given mask gradients . Args : grad_masks : B X 256 X 256 numpy array Returns : grad_vertices : B X N X 3 numpy array
function: def backward_mask(self, grad_masks):
          ''' Compute gradient of vertices given mask gradients.
          Args:
              grad_masks: B X 256 X 256 numpy array
          Returns:
              grad_vertices: B X N X 3 numpy array
          '''
          self.masks.grad = chainer.cuda.to_gpu(grad_masks, self.cuda_device)
          self.masks.backward()
          return self.vertices.grad.get()
function_tokens: def backward_mask ( self , grad_masks ) : self . masks . grad = chainer . cuda . to_gpu ( grad_masks , self . cuda_device ) self . masks . backward ( ) return self . vertices . grad . get ( )