Add a simple Module trait and implement it for the various nn layers (#500)

* Start adding the module trait.

* Use the module trait.

* Implement module for qmatmul.

1 files changed, 1 insertions, 1 deletions

diff --git a/candle-examples/examples/llama_multiprocess/model.rs b/candle-examples/examples/llama_multiprocess/model.rs
index fa8f9abf..1e7cafa2 100644
--- a/candle-examples/examples/llama_multiprocess/model.rs
+++ b/candle-examples/examples/llama_multiprocess/model.rs
@@ -1,6 +1,6 @@
 use candle::backend::BackendStorage;
 use candle::{CpuStorage, CustomOp1, DType, Device, IndexOp, Layout, Result, Shape, Tensor, D};
-use candle_nn::{rms_norm, Embedding, Linear, RmsNorm, VarBuilder};
+use candle_nn::{rms_norm, Embedding, Linear, Module, RmsNorm, VarBuilder};
 use cudarc::nccl::safe::{Comm, ReduceOp};
 use half::f16;
 use std::rc::Rc;