Get device correctly when module returns a dict instead of individual tensor

[shifangx]

What does this PR do ?

Issue description

When the model contains a MoE layer (or MTP layer), the device of the MoE loss scale (or MTP loss scale) needs to be set according to the device of the output tensor.
However, a problem occurs when trying to obtain the device of the output tensor for multimodule schedule.

Root cause

Normally, the forward function returns the output as a tensor.
But under the multi‑module schedule, the forward function returns the output as a dictionary, so the way we get the output device needs to be updated accordingly.

How to fix

This fix checks whether output is a dictionary. If it is, it takes the first value from the dict and gets its device.
Otherwise, it directly gets the device from output tensor.
This ensures consistent device extraction regardless of output format.

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[shifangx]

/ok to test

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/ok to test

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[shifangx]

/ok to test 7285cf0

[shifangx]

/ok to test 6217ab5

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