bitorch_engine.utils.model_helper

Functions

binary_matmul_forward_post_processing	Post-processes the output tensor of a binary matrix multiplication operation.
flatten_x	Flattens a 3D tensor into a 2D tensor by combining the first two dimensions.
init_weight	Initializes binary parameters using pre-trained weights if available.
load_checkpoint	Loads a checkpoint into a given model.
pack_bie_layers	Packs the weights of quantization layers in a given model to prepare for efficient storage.
pad_embedding_dim	This function takes as input a PyTorch tensor "weight" representing the embedding matrix, and pads its embedding dimension to the smallest multiple of 8 that is greater than or equal to the current embedding dimension.
pad_last_2_dims_to_multiple_of_128	Pad the last two dimensions of a PyTorch tensor to the nearest multiple of 128.
prepare_bie_layers	Prepares binary and n-bit quantized layers within a given model for training or inference.
qweight_update_fn	This method defines how to update quantized weights with quantized gradients.
save_checkpoint	Saves the state of a quantized PyTorch model in a bit-packed format.
unflatten_x	Unflattens a 2D tensor back into a 3D tensor using the original shape, reversing the operation performed by flatten_x.
update_zeros	Updates the zeros attribute of the qweight object based on its layer type.