self.qkv_gemm_func returns ValueError: The deleter and context arguments are mutually exclusive.

Describe the bug
I am getting the following error while attempting to run deepspeed-chat step 3 with the actor model CarperAI/openai_summarize_tldr_sft (gpt-j 6B) and critic model CarperAI/openai_summarize_tldr_rm_checkpoint (gpt-j 6B) and ZeRO stage level 2.

Traceback (most recent call last):
File "main.py", line 523, in
main()
File "main.py", line 430, in main
out = trainer.generate_experience(prompts)
File "/data/nt12_ssd_gluster/myself/yts/dc/training/step3_rlhf_finetuning/ppo_trainer.py", line 97, in generate_experience
seq = self._generate_sequence(prompts)
File "/data/nt12_ssd_gluster/myself/yts/dc/training/step3_rlhf_finetuning/ppo_trainer.py", line 75, in _generate_sequence
seq = self.actor_model.module.generate(prompts, max_length=max_min_length, min_length=max_min_length)
File "/data/nt12_ssd_gluster/myself/yts/dc/training/step1_supervised_finetuning/DeepSpeed/deepspeed/runtime/hybrid_engine.py", line 254, in generate
generate_ret_vals = self._generate(*inputs, **kwargs)
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/transformers/generation/utils.py", line 1437, in generate
return self.greedy_search(
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/transformers/generation/utils.py", line 2248, in greedy_search
outputs = self(
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/transformers/models/gptj/modeling_gptj.py", line 852, in forward
transformer_outputs = self.transformer(
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/transformers/models/gptj/modeling_gptj.py", line 687, in forward
outputs = block(
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/data/nt12_ssd_gluster/myself/yts/dc/training/step1_supervised_finetuning/DeepSpeed/deepspeed/model_implementations/transformers/ds_transformer.py", line 147, in forward
self.attention(input,
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/data/nt12_ssd_gluster/myself/yts/dc/training/step1_supervised_finetuning/DeepSpeed/deepspeed/ops/transformer/inference/ds_attention.py", line 152, in forward
qkv_out = self.qkv_func(input=input,
File "/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1102, in _call_impl
return forward_call(*input, **kwargs)
File "/data/nt12_ssd_gluster/myself/yts/dc/training/step1_supervised_finetuning/DeepSpeed/deepspeed/ops/transformer/inference/op_binding/qkv_gemm.py", line 35, in forward
output = self.qkv_gemm_func(input, weight, q_scale, bias, gamma, beta, self.config.epsilon, add_bias,
ValueError: The deleter and context arguments are mutually exclusive.

ds_report output

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

async_io ............... [YES] ...... [OKAY]
cpu_adagrad ............ [YES] ...... [OKAY]
cpu_adam ............... [YES] ...... [OKAY]
fused_adam ............. [YES] ...... [OKAY]
fused_lamb ............. [YES] ...... [OKAY]
quantizer .............. [YES] ...... [OKAY]
random_ltd ............. [YES] ...... [OKAY]
sparse_attn ............ [YES] ...... [OKAY]
spatial_inference ...... [YES] ...... [OKAY]
transformer ............ [YES] ...... [OKAY]
stochastic_transformer . [YES] ...... [OKAY]
transformer_inference .. [YES] ...... [OKAY]
utils .................. [YES] ...... [OKAY]

DeepSpeed general environment info:
torch install path ............... ['/data/nt12_ssd_gluster/myself/miniconda3/lib/python3.8/site-packages/torch']
torch version .................... 1.10.0+cu113
deepspeed install path ........... ['/data/nt12_ssd_gluster/myself/yts/dc/training/step1_supervised_finetuning/DeepSpeed/deepspeed']
deepspeed info ................... 0.9.1+cc67f22f, cc67f22f, master
torch cuda version ............... 11.3
torch hip version ................ None
nvcc version ..................... 11.3
deepspeed wheel compiled w. ...... torch 1.10, cuda 11.3

System info (please complete the following information):

• OS: Ubuntu 18.04
• GPU count and types: single node 8*A100
• Deepspeed version: 0.9.1+cc67f22f
• Python version: 3.8
• The installation of Deepspeed is completed by running

TORCH_CUDA_ARCH_LIST="8.0" DS_BUILD_OPS=1 pip install . 
TORCH_CUDA_ARCH_LIST="8.0" DS_BUILD_OPS=1 pip install -e .

Additional context
I would like to know if the pull request in https://github.com/microsoft/DeepSpeed/pull/3256 or some similar fixes can help with this issue.