fix

Before we where using `module.op().writeBytecode(writer)` to compute the
hash of a model
but it crashes on some inputs, notably for unused variables.

So I used the text representation of the mlir.

zml/module.zig

@@ -813,8 +813,11 @@ fn computeModuleHash(platform: Platform, module: mlir.Module) u64 {
     const writer = hasher_writer.writer();
 
     // Hash the canonicalized IR, without debug information that can change across builds.
-    module.op().writeBytecode(writer);
+    module.op().print(writer, .{ .debug_info = false });
-    //module.op().print(writer, .{ .debug_info = false });
+    // Note: before we where using module.op().writeBytecode(writer),
+    // but it crashes on some inputs, notably for unused variables.
+    // So we use the text representation of the mlir.
+    // See https://github.com/zml/zml/issues/97.
     // Writes can't fail because we are writing to a hasher.
     writer.writeAll(platform.pjrt_client.getPlatformName(platform.pjrt_api)) catch unreachable;
     const api_version = platform.pjrt_api.version();

zml/tensor.zig

@@ -4040,3 +4040,19 @@ test transposeIsJustAReshape {
     try std.testing.expect(!transposeIsJustAReshape(Shape.init(.{ 1, 10, 155, 1 }, .f32), &.{ 0, 2, 3, 1 }));
     try std.testing.expect(transposeIsJustAReshape(Shape.init(.{ 1, 10, 155, 1 }, .f32), &.{ 0, 1, 3, 2 }));
 }
+
+test "unused tensor" {
+    const zml = @import("zml.zig");
+    const platform = zml.testing.env();
+
+    const Local = struct {
+        pub fn forward(x: Tensor) Tensor {
+            const y = x.addConstant(1);
+            _ = y;
+            return x;
+        }
+    };
+
+    const mod = try zml.compileFn(std.testing.allocator, Local.forward, .{Shape.init(.{10}, .f32)}, platform);
+    defer mod.deinit();
+}