code: def forward(ctx, Q, cos, sin):
      cos, sin = cos.squeeze(), sin.squeeze()
      batch, seq_len, n_heads, head_dim = Q.shape
      Q = Q.view(batch * seq_len, n_heads * head_dim)
      n_rows, n_cols = Q.shape
      assert seq_len <= cos.shape[0]
  
      # [TODO] Changing blocksize to head_dim//2 seems to have
      # some concurrency / un-deterministic issues.
      BLOCK_SIZE, num_warps = calculate_settings(
          head_dim
      )  # (head_dim//2)
      _rope_embedding[
          (
              n_rows,
              n_heads,
          )
      ](
          Q,
          Q.stride(0),
          cos,
          cos.stride(0),
          sin,
          sin.stride(0),
          seq_len,
          head_dim,
          BACKWARD_PASS=False,
          BLOCK_SIZE=BLOCK_SIZE,
          num_warps=num_warps,
      )
      ctx.BLOCK_SIZE = BLOCK_SIZE
      ctx.num_warps = num_warps
      ctx.cos = cos
      ctx.sin = sin
      return Q.view(batch, seq_len, n_heads, head_dim)
  
file_path: unsloth/unsloth/kernels/rope_embedding.py
imports: import triton
  import triton.language
  import torch
  from .utils import calculate_settings
label_desc: Use image node_id 1 for calling the Fast_RoPE_Embedding obj's underlying member method code with example usage: obj.forward(ctx, Q, cos, sin) and returns: Q