Question about RoPE implementation: Possible shape mismatch?

I was looking into the RoPE implementation for ERNIE-Image and noticed something interesting that I wanted to double-check with you.

It looks like the `freqs_cis` tensor uses an **interleaved** format (e.g., repeating pairs like `[1.0, 1.0, 0.707, 0.707...]`), but the actual rotation logic uses Megatron-style **blocked** chunking. Here is the snippet for context:

```python
# Apply RoPE: same rotate_half logic as Megatron _apply_rotary_pos_emb_bshd (rotary_interleaved=False)
# x_in: [B, S, heads, head_dim], freqs_cis: [B, S, 1, head_dim] with angles [θ0,θ0,θ1,θ1,...]
def apply_rotary_emb(x_in: torch.Tensor, freqs_cis: torch.Tensor) -> torch.Tensor:
rot_dim = freqs_cis.shape[-1]
x, x_pass = x_in[..., :rot_dim], x_in[..., rot_dim:]
cos_ = torch.cos(freqs_cis).to(x.dtype)
sin_ = torch.sin(freqs_cis).to(x.dtype)
# Non-interleaved rotate_half: [-x2, x1]
x1, x2 = x.chunk(2, dim=-1)
x_rotated = torch.cat((-x2, x1), dim=-1)
return torch.cat((x * cos_ + x_rotated * sin_, x_pass), dim=-1)
```

If I am understanding the code correctly, applying interleaved frequencies to `[-x2, x1]` blocks means the two halves of a coordinate pair might be rotated by different angles. For example, the first element `x[0]` gets paired with `-x[D/2]` and multiplied by `theta_0`, but `x[D/2]` gets paired with `x[0]` and multiplied by `theta_{D/4}`.

Is this asymmetric rotation a known behavior from training, or am I missing something about how this specific implementation is supposed to work mathematically? I tried changing the alignment so the frequencies match the blocks, and as expected, the model's output turns into garbage.

Start at the apply_rotary_emb entry point and inspect how freqs_cis is constructed and passed into it. Compare the interleaved frequency layout with the blocked rotate_half operation, then use the reported output change as a behavioral check; done means resolving whether the mismatch is intentional or requires a documented correction.

Written by the indexing model from the issue text.