[Dy2St] Optimize int(Value) and float(Value) error messages

[gouzil]

PR Category

Execute Infrastructure

PR Types

Improvements

Description

新的 float(Value) 报错信息

TypeError: float(Tensor) is not supported in static graph mode. Because it's value is not available during the static mode.
If you haven't call float(Tensor) explicitly, it's usually triggered by the logging implicitly, for example:
    >>> logging.info("The value of x is: {float(x)}")
                                                ^ `x` is Tensor, `float(x)` triggers float(Tensor)

    There are two common workarounds available:
    If you are logging Tensor values, then consider logging only at dynamic graphs, for example:

        Modify the following code
        >>> logging.info("The value of x is: {float(x)}")
        to
        >>> if paddle.in_dynamic_mode():
        ...     logging.info("The value of x is: {float(x)}")

    If you need to convert the Tensor type, for example:
        Modify the following code
        >>> x = float(x)
        to
        >>> x = x.astype("float64")

新的 int(Value) 报错信息

TypeError: int(Tensor) is not supported in static graph mode. Because it's value is not available during the static mode.
If you haven't call int(Tensor) explicitly, it's usually triggered by the logging implicitly, for example:
    >>> logging.info("The value of x is: {int(x)}")
                                              ^ `x` is Tensor, `int(x)` triggers int(Tensor)

    There are two common workarounds available:
    If you are logging Tensor values, then consider logging only at dynamic graphs, for example:

        Modify the following code
        >>> logging.info("The value of x is: {int(x)}")
        to
        >>> if paddle.in_dynamic_mode():
        ...     logging.info("The value of x is: {int(x)}")

    If you need to convert the Tensor type, for example:
        Modify the following code
        >>> x = int(x)
        to
        >>> x = x.astype("int64")

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