Engram TileLang gate kernel does not match original Engram Pytorch Demo

In PyTorch Engram, the module returns only the Engram contribution:

```python
value = gates * self.value_proj(embeddings).unsqueeze(2)
output = value + self.short_conv(value)
return output
```

Reference:

https://github.com/deepseek-ai/Engram/blob/fb7f84a21f91223715394a33a1dc24bbfb7f788e/engram_demo_v1.py#L376-L378

The residual add with `hidden_states` happens outside the Engram module:

```python
hidden_states = self.engram(hidden_states=hidden_states,input_ids=input_ids) + hidden_states
```

Reference:

https://github.com/deepseek-ai/Engram/blob/fb7f84a21f91223715394a33a1dc24bbfb7f788e/engram_demo_v1.py#L389-L391

But the TileLang gate kernel adds `hidden_states` inside the kernel，even before short conv:

```python
output[i_s, pid_h, sub_base + thread_idx * vec_size + i_k] = x_local[i_k] + gate_score_reducer[0] * v_local[i_k]
```

Reference:

https://github.com/deepseek-ai/TileKernels/blob/36d9e45d38e204ebb87e6f6e833821eee0482fe5/tile_kernels/engram/engram_gate_kernel.py#L176-L177

So the two implementations differ:

```python
# PyTorch Engram
engram_output = gate * value + short_conv(gate * value)
hidden_states = hidden_states + engram_output
```

```python
# TileLang gate kernel
gate_output = hidden_states + gate * value
```

This makes the TileLang kernel inconsistent with the PyTorch Engram op. The gate kernel should output only:

```python
output = gate * value
```

if it is intended to match the PyTorch Engram module semantics.