[QUESTION]Why are inputs to ColumnParallelLinear different across ranks in register_forward_hook and register_forward_pre_hook

Hi Megatron-LM team,

I’m trying to check the input consistency of ColumnParallelLinear across tensor parallel ranks.
Specifically, I registered both a register_forward_hook and a register_forward_pre_hook to capture the input tensors on each rank.

However, when I compare the inputs captured by these hooks on different tensor parallel ranks, I find that they become different after some iterations.

Here is the code I use to check the input consistency across ranks:
```
def check_input_same(
module: torch.nn.Module,
input_: list[torch.Tensor],
output: list[torch.Tensor] | None = None,
) -> None:
"""Hook for saving the input during the forward pass of a module."""
input_tensor = input_[0] if isinstance(input_, list) else input_
input_tensor = input_tensor[0]
all_input = input_tensor.clone().detach()
torch.distributed.all_reduce(all_input)
if torch.allclose(all_input, input_tensor * torch.distributed.get_world_size(), rtol=1e-5, atol=1e-5):
print(f"Input is the same at layer {self._layers[module][0]} at hook.")
else:
print(f"Input is NOT the same at layer {self._layers[module][0]} at hook.")
```

My understanding was that ColumnParallelLinear is supposed to receive identical input on all tensor parallel ranks.
Why would the input tensors captured by register_forward_hook and register_forward_pre_hook be different on different ranks?

Is this expected, or does it indicate a problem in my pipeline or configuration?

Thank you for your time and help!

Best regards,