[BUG] Unused params lead to "still have inflight params" error

Bug description
Context: Running inference on a multi-modal LLM , at each decoding step parts of the network are used and depends on the input modality at each step. In my second step, deepspeed goes ahead and fetches part of the network that ends up not being used. The code does assume that this can happen and correctly invalidates the trace. However, for the params that were prefetched but never used, at the end of the step, these are detected as in-flight and result in the RuntimeError(f"still have inflight params").

To Reproduce
My setup is a bit involved. I am thinking it is clear from the description what the issue is. However, if the team feels like they can benefit from a simple reproduction, I can work on creating one. Please let me know.

Expected behavior
I would have expected that when we notice the order of params isn't the same as before, it would be reasonable to also not demand that all the parameters be used. Right now, we tolerate different ordering but require that all the params previously used (hence prefetched) need to be used at some point.

ds_report output

Setting ds_accelerator to cuda (auto detect)--------------------------------------------------DeepSpeed C++/CUDA extension op report
--------------------------------------------------
NOTE: Ops not installed will be just-in-time (JIT) compiled at      runtime if needed. Op compatibility means that your system
      meet the required dependencies to JIT install the op.
--------------------------------------------------
JIT compiled ops requires ninja
ninja .................. [OKAY]
--------------------------------------------------
op name ................ installed .. compatible
--------------------------------------------------
 [WARNING]  async_io requires the dev libaio .so object and headers but these were not found.
 [WARNING]  async_io: please install the libaio-devel package with yum
 [WARNING]  If libaio is already installed (perhaps from source), try setting the CFLAGS and LDFLAGS environment variables to where it can be found.
async_io ............... [NO] ....... [NO]
cpu_adagrad ............ [NO] ....... [OKAY]
cpu_adam ............... [NO] ....... [OKAY]
fused_adam ............. [NO] ....... [OKAY]fused_lamb ............. [NO] ....... [OKAY]
quantizer .............. [NO] ....... [OKAY]
random_ltd ............. [NO] ....... [OKAY]
 [WARNING]  please install triton==1.0.0 if you want to use sparse attention
sparse_attn ............ [NO] ....... [NO]
spatial_inference ...... [NO] ....... [OKAY]
transformer ............ [NO] ....... [OKAY]
stochastic_transformer . [NO] ....... [OKAY]
transformer_inference .. [NO] ....... [OKAY]
--------------------------------------------------
No CUDA runtime is found, using CUDA_HOME='/usr/local/cuda-11.6'
DeepSpeed general environment info:
torch install path ............... ['/home/ec2-user/anaconda3/envs/pytorch_p39/lib/python3.9/site-packages/torch']
torch version .................... 1.13.0
deepspeed install path ........... ['/home/ec2-user/anaconda3/envs/pytorch_p39/lib/python3.9/site-packages/deepspeed']
deepspeed info ................... 0.10.0, unknown, unknown
torch cuda version ............... 11.7
torch hip version ................ None
nvcc version ..................... 11.6
deepspeed wheel compiled w. ...... torch 1.13, cuda 11.7

System info (please complete the following information):

• OS: AL2 (Amazon Linux) 5.10.149-133.644.amzn2.x86_64 #1 SMP Tue Oct 18 16:52:42 UTC 2022 x86_64 x86_64 x86_64 GNU/Linux
• GPU count and types: p3.16xlarge instance from aws, 8 V100 with 16 GB per device
• Deepspeed version: 0.10.0
• (if applicable) Hugging Face Transformers/Accelerate/etc. versions: transformers: 4.29.1 accelerate 0.21.0
• Python version: 3.9.15