Function _format_tensor

python/paddle/tensor/to_string.py:181–252

Format a tensor Args: var(Tensor): The tensor to be formatted. summary(bool): Do summary or not. If true, some elements will not be printed, and be replaced with "...". indent(int): The indent of each line. max_width(int): The max width of each elements in v

(var, summary, indent=0, max_width=0, signed=False)

def _format_tensor(var, summary, indent=0, max_width=0, signed=False):
    """
    Format a tensor

    Args:
        var(Tensor): The tensor to be formatted.
        summary(bool): Do summary or not. If true, some elements will not be printed, and be replaced with "...".
        indent(int): The indent of each line.
        max_width(int): The max width of each elements in var.
        signed(bool): Print +/- or not.
    """
    edgeitems = DEFAULT_PRINT_OPTIONS.edgeitems
    linewidth = DEFAULT_PRINT_OPTIONS.linewidth

    if len(var.shape) == 0:
        # 0-D Tensor, whose shape = [], should be formatted like this.
        return _format_item(var, max_width, signed)
    elif len(var.shape) == 1:
        item_length = max_width + 2
        items_per_line = max(1, (linewidth - indent) // item_length)

        if summary and var.shape[0] > 2 * edgeitems:
            items = (
                [
                    _format_item(var[i], max_width, signed)
                    for i in range(edgeitems)
                ]
                + ['...']
                + [
                    _format_item(var[i], max_width, signed)
                    for i in range(var.shape[0] - edgeitems, var.shape[0])
                ]
            )
        else:
            items = [
                _format_item(var[i], max_width, signed)
                for i in range(var.shape[0])
            ]
        lines = [
            items[i : i + items_per_line]
            for i in range(0, len(items), items_per_line)
        ]
        s = (',\n' + ' ' * (indent + 1)).join(
            [', '.join(line) for line in lines]
        )
        return '[' + s + ']'
    else:
        # recursively handle all dimensions
        if summary and var.shape[0] > 2 * edgeitems:
            vars = (
                [
                    _format_tensor(
                        var[i], summary, indent + 1, max_width, signed
                    )
                    for i in range(edgeitems)
                ]
                + ['...']
                + [