parameters: (op)
return_statement: return [tensor_shape.TensorShape([num_points, num_classes - 1])]
docstring: Shape function for TreePredictions Op.
docstring_summary: Shape function for TreePredictions Op.
docstring_tokens: Shape function for TreePredictions Op .
function: def TreePredictions(op):
    """Shape function for TreePredictions Op."""
    num_points = op.inputs[0].get_shape()[0].value
    sparse_shape = op.inputs[3].get_shape()
    if sparse_shape.ndims > 0:
      num_points = None
    num_classes = op.inputs[7].get_shape()[1].value
  
    # The output of TreePredictions is
    # [node_pcw(evaluate_tree(x), c) for c in classes for x in input_data].
    return [tensor_shape.TensorShape([num_points, num_classes - 1])]
function_tokens: def TreePredictions ( op ) : num_points = op . inputs [ 0 ] . get_shape ( ) [ 0 ] . value sparse_shape = op . inputs [ 3 ] . get_shape ( ) if sparse_shape . ndims > 0 : num_points = None num_classes = op . inputs [ 7 ] . get_shape ( ) [ 1 ] . value # The output of TreePredictions is # [node_pcw(evaluate_tree(x), c) for c in classes for x in input_data]. return [ tensor_shape . TensorShape ( [ num_points , num_classes - 1 ] ) ]