(model, input_shapes: Optional[TensorShapes] = None)
return generate_specific_rand_input(model, full_input_shapes)
Generate random array for all inputs of a model
Generate random array for all inputs of a model
Generate random array for all inputs of a model
def generate_all_rand_input(model, input_shapes: Optional[TensorShapes] = None):
    """
    Generate random array for all inputs of a model
    """
    if input_shapes is None:
        input_shapes = {}
    input_names = get_input_names(model)
    full_input_shapes = {ipt: get_shape(model, ipt) for ipt in input_names}
    assert None not in input_shapes
    full_input_shapes.update(input_shapes)  # type: ignore
    return generate_specific_rand_input(model, full_input_shapes)
def generate_all_rand_input ( model , input_shapes : Optional [ TensorShapes ] = None ) : if input_shapes is None : input_shapes = { } input_names = get_input_names ( model ) full_input_shapes = { ipt : get_shape ( model , ipt ) for ipt in input_names } assert None not in input_shapes full_input_shapes . update ( input_shapes ) # type: ignore return generate_specific_rand_input ( model , full_input_shapes )