unsloth_compiled_cache/RMSNorm.py

"""
2025.3.17
2025.3.19
4.50.0
0.15.2
__UNSLOTH_VERSIONING__
"""

# Unsloth Zoo - Utilities for Unsloth
# Copyright 2023-present Daniel Han-Chen, Michael Han-Chen & the Unsloth team. All rights reserved.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU Lesser General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU Lesser General Public License
# along with this program.  If not, see <https://www.gnu.org/licenses/>.

import os
import importlib.util
if importlib.util.find_spec("unsloth_studio") is None:
    UNSLOTH_STUDIO_ENABLED = False
else:
    UNSLOTH_STUDIO_ENABLED = os.environ.get("UNSLOTH_STUDIO_DISABLED", "0") == "0"
pass
from typing import List, Dict, Tuple, Optional, Any, Callable
import math

torch_compile_options = {'epilogue_fusion': True, 'max_autotune': False, 'shape_padding': True, 'trace.enabled': False, 'triton.cudagraphs': False}
from torch import Tensor
import torch
import torch.nn as nn
from torch.nn import functional as F
from transformers.models.gemma3.modeling_gemma3 import (torch)

def forward(self, x: torch.Tensor) -> torch.Tensor:
    """
    Runs forward pass.
    """
    return F.rms_norm(x, self.normalized_shape, self.weight, self.eps).to(input.dtype).to(input.dtype)