mmengine.model

Module

BaseModule	Base module for all modules in openmmlab.
ModuleDict	ModuleDict in openmmlab.
ModuleList	ModuleList in openmmlab.
Sequential	Sequential module in openmmlab.

Model

BaseModel	Base class for all algorithmic models.
BaseDataPreprocessor	Base data pre-processor used for copying data to the target device.
ImgDataPreprocessor	Image pre-processor for normalization and bgr to rgb conversion.
BaseTTAModel	Base model for inference with test-time augmentation.

EMA

BaseAveragedModel	A base class for averaging model weights.
ExponentialMovingAverage	Implements the exponential moving average (EMA) of the model.
MomentumAnnealingEMA	Exponential moving average (EMA) with momentum annealing strategy.
StochasticWeightAverage	Implements the stochastic weight averaging (SWA) of the model.

Model Wrapper

MMDistributedDataParallel	A distributed model wrapper used for training,testing and validation in loop.
MMSeparateDistributedDataParallel	A DistributedDataParallel wrapper for models in MMGeneration.
MMFullyShardedDataParallel	A wrapper for sharding Module parameters across data parallel workers.

is_model_wrapper

Check if a module is a model wrapper.

Weight Initialization

BaseInit
Caffe2XavierInit
ConstantInit	Initialize module parameters with constant values.
KaimingInit	Initialize module parameters with the values according to the method described in the paper below.
NormalInit	Initialize module parameters with the values drawn from the normal distribution \(\mathcal{N}(\text{mean}, \text{std}^2)\).
PretrainedInit	Initialize module by loading a pretrained model.
TruncNormalInit	Initialize module parameters with the values drawn from the normal distribution \(\mathcal{N}(\text{mean}, \text{std}^2)\) with values outside \([a, b]\).
UniformInit	Initialize module parameters with values drawn from the uniform distribution \(\mathcal{U}(a, b)\).
XavierInit	Initialize module parameters with values according to the method described in the paper below.

bias_init_with_prob	Initialize conv/fc bias value according to a given probability value.
caffe2_xavier_init
constant_init
initialize	Initialize a module.
kaiming_init
normal_init
trunc_normal_init
uniform_init
update_init_info	Update the _params_init_info in the module if the value of parameters are changed.
xavier_init

Utils

detect_anomalous_params
merge_dict	Merge all dictionaries into one dictionary.
stack_batch	Stack multiple tensors to form a batch and pad the tensor to the max shape use the right bottom padding mode in these images.
revert_sync_batchnorm	Helper function to convert all SyncBatchNorm (SyncBN) and mmcv.ops.sync_bn.SyncBatchNorm`(MMSyncBN) layers in the model to `BatchNormXd layers.
convert_sync_batchnorm	Helper function to convert all BatchNorm layers in the model to SyncBatchNorm (SyncBN) or mmcv.ops.sync_bn.SyncBatchNorm (MMSyncBN) layers.