Files
2025-08-05 19:02:46 +08:00

80 lines
2.5 KiB
Python

# Copyright (c) Facebook, Inc. and its affiliates. All rights reserved.
#
# This source code is licensed under the BSD license found in the
# LICENSE file in the root directory of this source tree.
import logging
from dataclasses import dataclass
import torch
import torch.nn as nn
from xformers.components import Activation
from xformers.components.feedforward import (
Feedforward,
FeedforwardConfig,
register_feedforward,
)
logger = logging.getLogger("xformers")
if torch.cuda.is_available():
try:
from xformers.triton import FusedDropoutBias
@dataclass
class FusedMlpConfig(FeedforwardConfig):
hidden_layer_multiplier: int
@register_feedforward("FusedMLP", FusedMlpConfig)
class FusedMLP(Feedforward):
"""
A MLP using fused linear layers.
"""
def __init__(
self,
dim_model: int,
dropout: float,
activation: Activation,
hidden_layer_multiplier: int,
bias: bool = True,
*args,
**kwargs,
):
super().__init__()
dim_mlp = hidden_layer_multiplier * dim_model
self.mlp = nn.Sequential(
nn.Linear(
in_features=dim_model, out_features=dim_mlp, bias=False
), # bias is handled in the next layer
# pyre-ignore[16]: TODO(T101400990): Pyre did not recognize
# the `FusedLinear` import.
FusedDropoutBias(
p=dropout,
bias_shape=dim_mlp if bias else None,
activation=activation,
),
nn.Linear(
in_features=dim_mlp, out_features=dim_model, bias=False
), # bias is handled in the next layer
# pyre-ignore[16]: TODO(T101400990): Pyre did not recognize
# the `FusedLinear` import.
FusedDropoutBias(
p=dropout,
bias_shape=dim_model if bias else None,
activation=None,
),
)
self.requires_cuda = True
def forward(self, inputs: torch.Tensor) -> torch.Tensor:
return self.mlp(inputs)
except ImportError:
logger.warning("Triton is not available, FusedMLP will not be enabled.")