Move the VarMap to a separate file (#525)

* Move the var-map struct in a separate file.

* Fix some typos.

1 files changed, 87 insertions, 0 deletions

diff --git a/candle-nn/src/var_map.rs b/candle-nn/src/var_map.rs
new file mode 100644
index 00000000..f61fad23
--- /dev/null
+++ b/candle-nn/src/var_map.rs
@@ -0,0 +1,87 @@
+use candle::{safetensors::Load, DType, Device, Result, Shape, Tensor, Var};
+use std::collections::HashMap;
+use std::sync::{Arc, Mutex};
+
+/// A `VarMap` is a store that holds named variables. Variables can be retrieved from the stores
+/// and new variables can be added by providing some initialization config in case they are
+/// missing.
+/// `VarMap` structures can be serialized in the safetensors format.
+#[derive(Clone)]
+pub struct VarMap {
+    data: Arc<Mutex<HashMap<String, Var>>>,
+}
+
+impl VarMap {
+    /// Create a new empty `VarMap`.
+    #[allow(clippy::new_without_default)]
+    pub fn new() -> Self {
+        let data = Arc::new(Mutex::new(HashMap::new()));
+        Self { data }
+    }
+
+    /// Retrieve all the variables currently stored in the map.
+    pub fn all_vars(&self) -> Vec<Var> {
+        let tensor_data = self.data.lock().unwrap();
+        #[allow(clippy::map_clone)]
+        tensor_data.values().map(|c| c.clone()).collect::<Vec<_>>()
+    }
+
+    /// Save the map in the safetensors format.
+    pub fn save<P: AsRef<std::path::Path>>(&self, path: P) -> Result<()> {
+        let tensor_data = self.data.lock().unwrap();
+        let data = tensor_data.iter().map(|(k, v)| (k, v.as_tensor()));
+        safetensors::tensor::serialize_to_file(data, &None, path.as_ref())?;
+        Ok(())
+    }
+
+    /// Load some values from a safetensors file and modify the existing variables to have these
+    /// values.
+    ///
+    /// Note that values for variables that are currently not in the map are not kept.
+    pub fn load<P: AsRef<std::path::Path>>(&mut self, path: P) -> Result<()> {
+        let path = path.as_ref();
+        let data = unsafe { candle::safetensors::MmapedFile::new(path)? };
+        let data = data.deserialize()?;
+        let mut tensor_data = self.data.lock().unwrap();
+        for (name, var) in tensor_data.iter_mut() {
+            match data.tensor(name) {
+                Ok(data) => {
+                    let data: Tensor = data.load(var.device())?;
+                    if let Err(err) = var.set(&data) {
+                        candle::bail!("error setting {name} using data from {path:?}: {err}",)
+                    }
+                }
+                Err(_) => candle::bail!("cannot find tensor for {name}"),
+            }
+        }
+        Ok(())
+    }
+
+    /// Retrieve or add a new variable.
+    pub fn get<S: Into<Shape>>(
+        &self,
+        shape: S,
+        path: &str,
+        init: crate::Init,
+        dtype: DType,
+        device: &Device,
+    ) -> Result<Tensor> {
+        let shape = shape.into();
+        let mut tensor_data = self.data.lock().unwrap();
+        if let Some(tensor) = tensor_data.get(path) {
+            let tensor_shape = tensor.shape();
+            if &shape != tensor_shape {
+                candle::bail!("shape mismatch on {path}: {shape:?} <> {tensor_shape:?}")
+            }
+            return Ok(tensor.as_tensor().clone());
+        }
+        let var = init.var(shape, dtype, device)?;
+        let tensor = var.as_tensor().clone();
+        tensor_data.insert(path.to_string(), var);
+        Ok(tensor)
+    }
+
+    pub fn data(&self) -> &Mutex<HashMap<String, Var>> {
+        &self.data
+    }
+}