Start ML Coordinator.

Create some common data types and a fake executive. The fake executive
can either return an error (emulating execution failing) or a slice of
memory (emulating a correct result).

Change-Id: Id57f3ea3ee8db64b8921bf7446bcdf143d0daf49
GitOrigin-RevId: e266431d90864c0cd15567221acfa28a02c85a63

apps/system/components/MlCoordinator/Cargo.toml

@@ -0,0 +1,6 @@
+[workspace]
+
+members = [
+    "fake-executive",
+    "ml-common"
+]

apps/system/components/MlCoordinator/fake-executive/Cargo.toml

@@ -0,0 +1,8 @@
+[package]
+name = "fake-executive"
+version = "0.1.0"
+authors = ["Adam Jesionowski <jesionowski@google.com>"]
+edition = "2018"
+
+[dependencies]
+ml-common = { path = "../ml-common" }

apps/system/components/MlCoordinator/fake-executive/src/lib.rs

@@ -0,0 +1,44 @@
+use ml_common as ml;
+use ml_common::ExecutiveInterface;
+
+pub struct FakeExecutive {
+    output_memory: [u8; 512],
+    fake_error: Option<ml::ExecutionError>,
+}
+
+impl ml::ExecutiveInterface for FakeExecutive {
+    fn run_model(&self, _model: &ml::Model) -> Result<&[u8], ml::ExecutionError> {
+        match self.fake_error {
+            Some(err) => Err(err),
+            None => Ok(&self.output_memory),
+        }
+    }
+}
+
+#[test]
+fn return_ok() {
+    let exec = FakeExecutive {
+        output_memory: [0xAD; 512],
+        fake_error: None,
+    };
+    let model = ml::Model {
+        output_activations_len: 512,
+    };
+
+    let res = exec.run_model(&model);
+    assert!(res.is_ok());
+    assert_eq!(res.unwrap()[0], 0xAD)
+}
+
+#[test]
+fn return_err() {
+    let exec = FakeExecutive {
+        output_memory: [0; 512],
+        fake_error: Some(ml::ExecutionError::CoreReset),
+    };
+    let model = ml::Model {
+        output_activations_len: 512,
+    };
+
+    assert!(exec.run_model(&model).is_err());
+}

apps/system/components/MlCoordinator/ml-common/Cargo.toml

@@ -0,0 +1,5 @@
+[package]
+name = "ml-common"
+version = "0.1.0"
+authors = ["Adam Jesionowski <jesionowski@google.com>"]
+edition = "2018"

apps/system/components/MlCoordinator/ml-common/src/lib.rs

@@ -0,0 +1,17 @@
+// TODO(jesionowski): What are the actual errors we may encounter?
+#[derive(Copy, Clone, Debug)]
+pub enum ExecutionError {
+    InvalidInstruction,
+    InvalidFetch,
+    CoreReset
+}
+
+// The abstraction layer over the "hardware" of running an execution.
+// Returns a slice of bytes, which is the output data, or an ExecutionError.
+pub trait ExecutiveInterface {
+    fn run_model(&self, model: &Model) -> Result<&[u8], ExecutionError>;
+}
+
+pub struct Model {
+    pub output_activations_len: usize,
+}