Begin Refactoring LigandMPNN CLI Call to use Metal

ferritin-featurizers/Cargo.toml

@@ -8,10 +8,23 @@ description.workspace = true
 
 [dependencies]
 anyhow.workspace = true
-candle-core = "0.8"
+
+candle-metal-kernels = { git = "https://github.com/zachcp/candle.git", package = "candle-metal-kernels", branch = "20241201-SA" }
+candle-core = { git = "https://github.com/zachcp/candle.git", package = "candle-core", features = [
+    "metal",
+], branch = "20241201-SA" }
+
+# candle-core = { version = "0.8", features = ["metal"] }
 candle-hf-hub = "0.3.3"
-candle-nn = "0.8"
-candle-transformers = "0.8.0"
+
+# candle-nn = { version = "0.8", features = ["metal"] }
+candle-nn = { git = "https://github.com/zachcp/candle.git", package = "candle-nn", features = [
+    "metal",
+], branch = "20241201-SA" }
+candle-transformers = { git = "https://github.com/zachcp/candle.git", package = "candle-transformers", features = [
+    "metal",
+], branch = "20241201-SA" }
+# candle-transformers = "0.8.0"
 clap = "4.5.21"
 ferritin-core = { path = "../ferritin-core" }
 itertools.workspace = true

ferritin-featurizers/src/commands/run.rs

@@ -2,7 +2,30 @@ use crate::models::ligandmpnn::configs::{
     AABiasConfig, LigandMPNNConfig, MPNNExecConfig, MembraneMPNNConfig, ModelTypes, MultiPDBConfig,
     ResidueControl, RunConfig,
 };
-use candle_core::Device;
+use candle_core::utils::{cuda_is_available, metal_is_available};
+use candle_core::{Device, Result};
+
+pub fn device(cpu: bool) -> Result<Device> {
+    if cpu {
+        Ok(Device::Cpu)
+    } else if cuda_is_available() {
+        Ok(Device::new_cuda(0)?)
+    } else if metal_is_available() {
+        Ok(Device::new_metal(0)?)
+    } else {
+        #[cfg(all(target_os = "macos", target_arch = "aarch64"))]
+        {
+            println!(
+                "Running on CPU, to run on GPU(metal), build this example with `--features metal`"
+            );
+        }
+        #[cfg(not(all(target_os = "macos", target_arch = "aarch64")))]
+        {
+            println!("Running on CPU, to run on GPU, build this example with `--features cuda`");
+        }
+        Ok(Device::Cpu)
+    }
+}
 
 pub fn execute(
     seed: i32,
@@ -17,7 +40,7 @@ pub fn execute(
     multi_pdb_config: MultiPDBConfig,
 ) -> anyhow::Result<()> {
     // todo - whats the best way to handle device?
-    let device = &Device::Cpu;
+    let device = device(false)?;
 
     let model_type = model_type.unwrap_or(ModelTypes::ProteinMPNN);
 
@@ -37,6 +60,7 @@ pub fn execute(
     println!("About to Load the model!");
     let model = exec.load_model()?;
     println!("Model Loaded!");
+    println!("Model Loaded on the {:?}", model.device);
 
     println!("Generating Protein Features");
     let prot_features = exec.generate_protein_features()?;

ferritin-featurizers/src/models/ligandmpnn/configs.rs

@@ -35,14 +35,14 @@ pub struct MPNNExecConfig {
     pub(crate) membrane_mpnn_config: Option<MembraneMPNNConfig>,
     pub(crate) multi_pdb_config: Option<MultiPDBConfig>,
     pub(crate) residue_control_config: Option<ResidueControl>,
-    // device: &candle_core::Device,
+    pub(crate) device: Device,
     pub(crate) seed: i32,
 }
 
 impl MPNNExecConfig {
     pub fn new(
         seed: i32,
-        device: &Device,
+        device: Device,
         pdb_path: String,
         model_type: ModelTypes,
         run_config: RunConfig,
@@ -62,23 +62,25 @@ impl MPNNExecConfig {
             residue_control_config: residue_config,
             multi_pdb_config: multi_pdb_specific,
             seed,
-            // device: device,
+            device: device,
         })
     }
     // Todo: refactor this to use loader.
     pub fn load_model(&self) -> Result<ProteinMPNN, Error> {
+        let default_dtype = DType::F32;
+
         // this is a hidden dep....
         let (mpnn_file, _handle) = TestFile::ligmpnn_pmpnn_01().create_temp()?;
         let pth = PthTensors::new(mpnn_file, Some("model_state_dict"))?;
-        let vb = VarBuilder::from_backend(Box::new(pth), DType::F32, Device::Cpu);
+        let vb = VarBuilder::from_backend(Box::new(pth), default_dtype, self.device.clone());
         let pconf = ProteinMPNNConfig::proteinmpnn();
         Ok(ProteinMPNN::load(vb, &pconf).expect("Unable to load the PMPNN Model"))
     }
     pub fn generate_model(self) {
         todo!()
     }
     pub fn generate_protein_features(&self) -> Result<ProteinFeatures, Error> {
-        let device = Device::Cpu;
+        let device = self.device.clone();
         let base_dtype = DType::F32;
 
         // init the Protein Features

ferritin-featurizers/src/models/ligandmpnn/featurizer.rs

@@ -24,7 +24,7 @@ fn is_heavy_atom(element: &Element) -> bool {
 
 /// Convert the AtomCollection into a struct that can be passed to a model.
 pub trait LMPNNFeatures {
-    fn encode_amino_acids(&self, device: &Device) -> Result<(Tensor)>; // ( residue types )
+    fn encode_amino_acids(&self, device: &Device) -> Result<Tensor>; // ( residue types )
     fn featurize(&self, device: &Device) -> Result<ProteinFeatures>; // need more control over this featurization process
     fn get_res_index(&self) -> Vec<u32>;
     fn to_numeric_backbone_atoms(&self, device: &Device) -> Result<Tensor>; // [residues, N/CA/C/O, xyz]