Add Layer module; Add neuron activation unit test

flake.nix

@@ -1,61 +1,61 @@
 {
-  description = "Algorithmic (aka automatic) differentiation implementation in OCaml";
+	description = "Algorithmic (aka automatic) differentiation implementation in OCaml";
 
-  inputs = {
-    nixpkgs.url = "github:nixos/nixpkgs?ref=nixos-unstable";
-    flake-utils.url = "github:numtide/flake-utils";
-  };
+	inputs = {
+		nixpkgs.url = "github:nixos/nixpkgs?ref=nixos-unstable";
+		flake-utils.url = "github:numtide/flake-utils";
+	};
 
-  outputs = { self, nixpkgs, flake-utils, ... }:
-    flake-utils.lib.eachDefaultSystem (system:
-      let
-        pkgs = nixpkgs.legacyPackages.${system};
-        isDarwin = pkgs.stdenv.isDarwin;
-        # thanks to https://github.com/commercialhaskell/stack/issues/1698#issuecomment-178098712 for the idea
-        darwinFrameworks = pkgs.lib.optionals isDarwin (with pkgs.darwin.apple_sdk.frameworks; [
-          Cocoa
-          CoreServices
-        ]);
-        ocamlEnv = with pkgs.ocamlPackages; [
-          ocaml
-          utop
-          dune_3
-          findlib
-          ocaml-lsp
-          ocamlformat
-        ];
-      in
-      {
-        devShell = pkgs.mkShell {
-          buildInputs = ocamlEnv ++ [ pkgs.opam ] ++ darwinFrameworks;
-          shellHook = ''
-                    export IN_NIX_DEVELOP_SHELL=1
+	outputs = { self, nixpkgs, flake-utils, ... }:
+		flake-utils.lib.eachDefaultSystem (system:
+			let
+				pkgs = nixpkgs.legacyPackages.${system};
+				isDarwin = pkgs.stdenv.isDarwin;
+				# thanks to https://github.com/commercialhaskell/stack/issues/1698#issuecomment-178098712 for the idea
+				darwinFrameworks = pkgs.lib.optionals isDarwin (with pkgs.darwin.apple_sdk.frameworks; [
+					Cocoa
+					CoreServices
+				]);
+				ocamlEnv = with pkgs.ocamlPackages; [
+					ocaml
+					utop
+					dune_3
+					findlib
+					ocaml-lsp
+					ocamlformat
+				];
+			in
+			{
+				devShell = pkgs.mkShell {
+					buildInputs = ocamlEnv ++ [ pkgs.opam ] ++ darwinFrameworks;
+					shellHook = ''
+										export IN_NIX_DEVELOP_SHELL=1
 
-                    export OPAMROOT=$NIX_BUILD_TOP/.opam
-                    # unsetting the below env var is required for fixing a thorny issue with `num` install
-                    # similar issue & solution thread: https://github.com/ocaml/Zarith/issues/136 
-                    unset OCAMLFIND_DESTDIR
+										export OPAMROOT=$NIX_BUILD_TOP/.opam
+										# unsetting the below env var is required for fixing a thorny issue with `num` install
+										# similar issue & solution thread: https://github.com/ocaml/Zarith/issues/136 
+										unset OCAMLFIND_DESTDIR
 
-                    opam init --bare --disable-sandboxing -y --shell-setup -vv
-                    opam option -global depext=false
-                    OCAML_VERSION=$(ocaml --version | awk '{printf $5}')
-                    opam switch create $OCAML_VERSION
-                    eval $(opam env --switch=$OCAML_VERSION)
-                    opam install . --deps-only -y -v
+										opam init --bare --disable-sandboxing -y --shell-setup -vv
+										opam option -global depext=false
+										OCAML_VERSION=$(ocaml --version | awk '{printf $5}')
+										opam switch create $OCAML_VERSION
+										eval $(opam env --switch=$OCAML_VERSION)
+										opam install . --deps-only -y -v
 
-                    # figure out what the default shell of this computer is and set it
-            		  '' +
-          (if isDarwin then
-            ''
-                    SHELLY=$(dscl . -read /Users/$USER UserShell | awk '{print $2}')
-              			exec $SHELLY
-            ''
-          else
-            ''
-              SHELLY=$(getent passwd $USER | awk -F: '{printf $7}')
-              exec $SHELLY
-            '');
-        };
-      }
-    );
+										# figure out what the default shell of this computer is and set it
+									'' +
+					(if isDarwin then
+						''
+										SHELLY=$(dscl . -read /Users/$USER UserShell | awk '{print $2}')
+										exec $SHELLY
+						''
+					else
+						''
+							SHELLY=$(getent passwd $USER | awk -F: '{printf $7}')
+							exec $SHELLY
+						'');
+				};
+			}
+		);
 }

lib/dune

@@ -1,4 +1,4 @@
 (library
   (name smolgrad)
   (public_name smolgrad)
-  (modules variable neuron))
+  (modules variable neuron layer))

lib/layer.ml

@@ -0,0 +1,12 @@
+module Layer = struct
+  type t = {
+    neurons : Neuron.Neuron.t list
+  }
+
+  let create number_of_inputs number_of_neurons is_non_linear =
+    let neurons = List.init number_of_neurons (fun _ -> Neuron.Neuron.create number_of_inputs is_non_linear) in
+    { neurons = neurons }
+
+  let propagate_input (layer: t) input_vector =
+    List.map (fun neuron -> Neuron.Neuron.weigh_input neuron input_vector) layer.neurons
+end

lib/layer.mli

@@ -0,0 +1,11 @@
+(* Layer is the aggregator of many neurons parallelly
+   captures essence of an input by adjusting it's weights and biases *)
+module Layer : sig
+    type t
+
+    (* Constructor; constructs a layer of neurons *)
+    val create : int -> int -> bool -> t
+
+    (* Propagates the input across all the neurons in the layer *)
+    val propagate_input : t -> Variable.Variable.t list -> Variable.Variable.t list
+end

lib/neuron.ml

@@ -26,7 +26,8 @@ module Neuron = struct
     is_non_linear = is_non_linear;
   }
 
-  let weigh_inputs (neuron: t) input_vector =
+  (* TODO: Check for dimension-mismatch *)
+  let weigh_input (neuron: t) input_vector =
     (* one-to-one multiplication of inputs to their corresponding weights *)
     let weighted_sum = List.fold_left2 (fun accumulator weight_i input_i -> Variable.Variable.(accumulator + weight_i * input_i))
       (Variable.Variable.create 0.0) neuron.weights input_vector in

lib/neuron.mli

@@ -16,5 +16,5 @@ module Neuron : sig
     val create : int -> bool -> t
 
     (* Passes the training input and lets the neuron weigh the input values against its weights and biases *)
-    val weigh_inputs : t -> Variable.Variable.t list -> Variable.Variable.t
+    val weigh_input : t -> Variable.Variable.t list -> Variable.Variable.t
 end

test/neuron_operations.ml

@@ -1,9 +1,9 @@
 open Smolgrad.Neuron
+open Smolgrad.Variable
 
 let test_neuron_initialization () =
   let n = Neuron.create 5 true in
   let n_weights = (Neuron.parameters n).weights in
-  assert (Smolgrad.Variable.Variable.data (Neuron.parameters n).bias = 0.0);
 
   Alcotest.(check int)
     "Neuron: Right number of parameters are set"
@@ -19,7 +19,22 @@ let test_neuron_initialization () =
     List.for_all (fun x -> (Smolgrad.Variable.Variable.data x) >= -1.0 && (Smolgrad.Variable.Variable.data x) <= 1.0) weights in
 
   Alcotest.(check bool)
-    "Neuron: All weights are in range [-1, 1]"
+    "Neuron: All weights are in range [-1.0, 1.0]"
     true
     (are_weights_in_range n_weights);
 ;;
+
+let test_neuron_weights_reacting_to_input () =
+  let n = Neuron.create 3 false in
+
+  let neuron_activation_for_input_1 = Neuron.weigh_input n [Variable.create 3.0; Variable.create 2.0; Variable.create 1.0] in
+  let neuron_activation_for_input_2 = Neuron.weigh_input n [Variable.create 8.0; Variable.create 13.0; Variable.create (-4.0)] in
+
+  let n_weight_values = Array.of_list (List.map (fun x -> Variable.data x) (Neuron.parameters n).weights) in
+  let remainder = (3.0 -. 8.0) *. n_weight_values.(0) +. (2.0 -. 13.0) *. n_weight_values.(1) +. (1.0 -. (-4.0)) *. n_weight_values.(2) in
+
+  Alcotest.(check (float 0.01))
+    "Neuron: Neuron activation upon input happened correctly"
+    remainder
+    (Smolgrad.Variable.Variable.data neuron_activation_for_input_1 -. Smolgrad.Variable.Variable.data neuron_activation_for_input_2);
+;;

test/smolgrad_tests.ml

@@ -7,4 +7,5 @@ let () =
 
   (* unit tests for Neuron *)
   Neuron_operations.test_neuron_initialization ();
+  Neuron_operations.test_neuron_weights_reacting_to_input ();
 ;;