class_docstr: Local Implicit Grid layer.
    
docstr: Forward method for Learnable Voxel Grid.
  
  Args:
    grid: `[batch_size, *self.size, in_features]` tensor, input feature grid.
    pts: `[batch_size, num_points, dim]` tensor, coordinates of points that
    are within the range (0, 1).
    training: bool, flag indicating training phase.
  Returns:
    outputs: `[batch_size, num_points, out_features]` tensor, continuous
    function field value at locations specified at pts.
  Raises:
    RuntimeError: dimensions of grid does not match that of self.
code: def call(self, grid, pts, training=False):
      """Forward method for Learnable Voxel Grid.
  
      Args:
        grid: `[batch_size, *self.size, in_features]` tensor, input feature grid.
        pts: `[batch_size, num_points, dim]` tensor, coordinates of points that
        are within the range (0, 1).
        training: bool, flag indicating training phase.
      Returns:
        outputs: `[batch_size, num_points, out_features]` tensor, continuous
        function field value at locations specified at pts.
      Raises:
        RuntimeError: dimensions of grid does not match that of self.
      """
      # assert that dimensions match
      grid = tf.ensure_shape(
          grid,
          (None, self.size[0], self.size[1], self.size[2], self.cin),
      )
      pts = tf.ensure_shape(pts, (None, None, self.dim))
  
      lat, weights, xloc = self._interp(grid, pts)
      outputs = self._eval_net(lat, weights, xloc, training=training)
  
      return outputs
  
file_path: graphics/tensorflow_graphics/projects/local_implicit_grid/core/local_implicit_grid_layer.py
imports: import tensorflow.compat.v1
  from tensorflow_graphics.projects.local_implicit_grid.core import implicit_nets
  from tensorflow_graphics.projects.local_implicit_grid.core import regular_grid_interpolation
label_desc: Use image node_id 2 for calling the LocalImplicitGrid obj's underlying member method code with example usage: obj.call(grid, pts, training) and returns: outputs