def switch(condition, then_expression, else_expression):
    """Switches between two operations depending on a scalar value (int or bool).
    Note that both `then_expression` and `else_expression`
    should be symbolic tensors of the *same shape*.

    # Arguments
        condition: scalar tensor.
        then_expression: TensorFlow operation.
        else_expression: TensorFlow operation.
    """
    x_shape = copy.copy(then_expression.get_shape())
    x = tf.cond(tf.cast(condition, 'bool'),
                lambda: then_expression,
                lambda: else_expression)
    x.set_shape(x_shape)
    return x
def switch(condition, then_expression, else_expression):
    """Switches between two operations depending on a scalar value (int or bool).
    Note that both `then_expression` and `else_expression`
    should be symbolic tensors of the *same shape*.

    # Arguments
        condition: scalar tensor.
        then_expression: TensorFlow operation.
        else_expression: TensorFlow operation.
    """
    x_shape = copy.copy(then_expression.get_shape())
    x = tf.cond(tf.cast(condition, 'bool'),
                lambda: then_expression,
                lambda: else_expression)
    x.set_shape(x_shape)
    return x
def switch ( condition , then_expression , else_expression ) : x_shape = copy . copy ( then_expression . get_shape ( ) ) x = tf . cond ( tf . cast ( condition , 'bool' ) , lambda : then_expression , lambda : else_expression ) x . set_shape ( x_shape ) return x
Switches between two operations depending on a scalar value (int or bool).
    Note that both `then_expression` and `else_expression`
    should be symbolic tensors of the *same shape*.

    # Arguments
        condition: scalar tensor.
        then_expression: TensorFlow operation.
        else_expression: TensorFlow operation.
Switches between two operations depending on a scalar value ( int or bool ) . Note that both then_expression and else_expression should be symbolic tensors of the * same shape * .