Address likely package mismatch issues (#1634)

Summary:

Previous CI runs were encountering issues:

1. https://github.com/.../runs/16867033035/job/47776474001

```
E           torch.AcceleratorError: CUDA error: no kernel image is available for execution on the device
E           CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
E           For debugging consider passing CUDA_LAUNCH_BLOCKING=1
E           Compile with `TORCH_USE_CUDA_DSA` to enable device-side assertions.
```

2. https://github.com/pytorch/captum/actions/runs/16867033037/job/47775775171

`tests/attr/test_llm_attr_hf_compatibility.py:76: error: Argument 1 to "__call__" of "_Wrapped" has incompatible type "str"; expected "PreTrainedModel" [arg-type]`

This is likely due to (1) mismatched pytorch versions vs the cuda version 12.1 specified in test-pip-gpu.yml, triggered by [new PyTorch release](https://github.com/pytorch/pytorch/releases) and (2) lack of full typing causing error thrown by `mypy`, triggered by loosely defined `mypy>=0.760` probably pulling [new MyPy release](https://pypi.org/project/mypy/#history)

Differential Revision: D80120024

Author: Sharon Tan

.github/workflows/test-pip-gpu.yml

@@ -22,7 +22,9 @@ jobs:
       gpu-arch-version: ${{ matrix.cuda_arch_version }}
       script: |
         python3 -m pip install --upgrade pip --progress-bar off
-        python3 -m pip install -e .[dev] --progress-bar off
+        python3 -m pip install torch==2.5.1 torchvision==0.20.1 --index-url https://download.pytorch.org/whl/cu121
+        python3 -m pip install -e .[dev] --index-url https://download.pytorch.org/whl/cu121 --progress-bar off
+        python3 -m pip install transformers --progress-bar off
 
         # Build package
         python3 -m pip install build --progress-bar off

tests/attr/test_llm_attr_hf_compatibility.py

@@ -20,7 +20,7 @@
 HAS_HF = True
 try:
     # pyre-ignore[21]: Could not find a module corresponding to import `transformers`
-    from transformers import AutoModelForCausalLM, AutoTokenizer
+    from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedModel
 except ImportError:
     HAS_HF = False
 
@@ -69,7 +69,7 @@ def test_llm_attr_hf_compatibility(
         tokenizer = AutoTokenizer.from_pretrained(
             "hf-internal-testing/tiny-random-LlamaForCausalLM"
         )
-        llm = AutoModelForCausalLM.from_pretrained(
+        llm: PreTrainedModel = AutoModelForCausalLM.from_pretrained(
             "hf-internal-testing/tiny-random-LlamaForCausalLM"
         )