[BUG] `get_gpt_layer_local_spec` fails to initialize correct `DotProductAttention` in MLA mode

### Describe the Bug

The function `get_gpt_layer_local_spec` claims to support `multi_latent_attention=True`, but it fails to initialize a correct `DotProductAttention` instance. Specifically, it does not account for `k_channels` and `v_channels`, which are required for `MLASelfAttention`.

### To Reproduce

Run the following minimal script:

```python
import torch
from megatron.core import parallel_state
from megatron.core.models.gpt.gpt_layer_specs import get_gpt_layer_local_spec
from megatron.core.tensor_parallel import model_parallel_cuda_manual_seed
from megatron.core.transformer.enums import AttnMaskType
from megatron.core.transformer.multi_latent_attention import MLASelfAttention
from megatron.core.transformer.transformer_config import MLATransformerConfig

random_seed = 42
torch.distributed.init_process_group(
init_method="tcp://127.0.0.1:12340",
rank=0,
world_size=1,
)
parallel_state.initialize_model_parallel(1, 1)
model_parallel_cuda_manual_seed(random_seed)

if __name__ == "__main__":
config = MLATransformerConfig(
num_layers=1,
hidden_size=512,
num_attention_heads=8,
)

attention = MLASelfAttention(
config,
submodules=get_gpt_layer_local_spec(multi_latent_attention=True).submodules.self_attention.submodules,
layer_number=0,
attn_mask_type=AttnMaskType.causal,
)

```

### Expected Behavior

The call to `MLASelfAttention` should succeed when using the submodules from `get_gpt_layer_local_spec(multi_latent_attention=True)`.

### Environment

* **Megatron-LM commit**: `core_r0.11.0`
* **PyTorch version**: `2.6.0`
* **CUDA version**: `12.5`
* **NCCL version**: *2.21.5*

### 💡 Proposed Fix

The `DotProductAttention` module returned by the local spec should accept and properly initialize `k_channels` and `v_channels`, which are required for MLA-based attention mechanisms.