print input

Cargo.lock

@@ -5478,9 +5478,9 @@ dependencies = [
 
 [[package]]
 name = "strafesnet_graphics"
-version = "0.0.11-depth"
+version = "0.0.11-depth2"
 source = "sparse+https://git.itzana.me/api/packages/strafesnet/cargo/"
-checksum = "16266ca7e57ce802b7abd24c6cd8f9b8d95752f7eaead27e42b431b9768d6135"
+checksum = "829804ab9c167365e576de8ebd8a245ad979cb24558b086e693e840697d7956c"
 dependencies = [
  "bytemuck",
  "ddsfile",
@@ -5515,9 +5515,9 @@ dependencies = [
 
 [[package]]
 name = "strafesnet_roblox_bot_player"
-version = "0.6.2-depth"
+version = "0.6.2-depth2"
 source = "sparse+https://git.itzana.me/api/packages/strafesnet/cargo/"
-checksum = "12d1aa21c174f23f7f7ede583292a8c82e4b3c483fb0d950e58f84d52807f6ed"
+checksum = "f39e7dfc0cb23e482089dc7eac235ad4b274ccfdb8df7617889a90e64a1e247a"
 dependencies = [
  "glam",
  "strafesnet_common",

Cargo.toml

@@ -8,9 +8,9 @@ burn = { version = "0.20.1", features = ["cuda", "autodiff"] }
 wgpu = "29.0.0"
 
 strafesnet_common = { version = "0.9.0", registry = "strafesnet" }
-strafesnet_graphics = { version = "=0.0.11-depth", registry = "strafesnet" }
+strafesnet_graphics = { version = "=0.0.11-depth2", registry = "strafesnet" }
 strafesnet_physics = { version = "=0.0.2-surf", registry = "strafesnet" }
 strafesnet_roblox_bot_file = { version = "0.9.4", registry = "strafesnet" }
-strafesnet_roblox_bot_player = { version = "=0.6.2-depth", registry = "strafesnet" }
+strafesnet_roblox_bot_player = { version = "=0.6.2-depth2", registry = "strafesnet" }
 strafesnet_snf = { version = "0.4.0", registry = "strafesnet" }
 pollster = "0.4.0"

src/main.rs

@@ -1,7 +1,7 @@
 use burn::backend::Autodiff;
 use burn::nn::loss::{MseLoss, Reduction};
 use burn::nn::{Linear, LinearConfig, Relu};
-use burn::optim::{GradientsParams, Optimizer, SgdConfig};
+use burn::optim::{GradientsParams, Optimizer, AdamConfig};
 use burn::prelude::*;
 
 type InferenceBackend = burn::backend::Cuda<f32>;
@@ -14,13 +14,8 @@ use strafesnet_roblox_bot_file::v0;
 const SIZE_X: usize = 64;
 const SIZE_Y: usize = 36;
 const INPUT: usize = SIZE_X * SIZE_Y;
-const HIDDEN: [usize; 7] = [
-	INPUT >> 1,
-	INPUT >> 2,
+const HIDDEN: [usize; 2] = [
 	INPUT >> 3,
-	INPUT >> 4,
-	INPUT >> 5,
-	INPUT >> 6,
 	INPUT >> 7,
 ];
 // MoveForward
@@ -89,6 +84,9 @@ fn training() {
 		.unwrap();
 	let timelines =
 		strafesnet_roblox_bot_file::v0::read_all_to_block(std::io::Cursor::new(bot_file)).unwrap();
+	let bot = strafesnet_roblox_bot_player::bot::CompleteBot::new(timelines).unwrap();
+	let world_offset = bot.world_offset();
+	let timelines = bot.timelines();
 
 	// setup graphics
 	let desc = wgpu::InstanceDescriptor::new_without_display_handle_from_env();
@@ -235,6 +233,9 @@ fn training() {
 		fn a(a: v0::Vector3) -> [f32; 2] {
 			[a.y, a.x]
 		}
+		fn sub<T: core::ops::Sub>(lhs: T, rhs: T) -> T::Output {
+			lhs - rhs
+		}
 
 		let mut encoder = device.create_command_encoder(&wgpu::CommandEncoderDescriptor {
 			label: Some("wgpu encoder"),
@@ -244,7 +245,7 @@ fn training() {
 		graphics.encode_commands(
 			&mut encoder,
 			&graphics_texture_view,
-			p(output_event.event.position).into(),
+			sub(p(output_event.event.position).into(), world_offset),
 			a(output_event.event.angles).into(),
 		);
 
@@ -288,6 +289,7 @@ fn training() {
 		}
 		output_staging_buffer.unmap();
 
+		let inputs_start = inputs.len();
 		// discombolulate stride
 		for y in 0..size.y {
 			inputs.extend(
@@ -297,6 +299,8 @@ fn training() {
 					.map(|b| f32::from_le_bytes(b.try_into().unwrap())),
 			)
 		}
+		let inputs_end = inputs.len();
+		println!("inputs = {:?}", &inputs[inputs_start..inputs_end]);
 
 		texture_data.clear();
 	}
@@ -306,7 +310,7 @@ fn training() {
 	let mut model: Net<TrainingBackend> = Net::init(&device);
 	println!("Training model ({} parameters)", model.num_params());
 
-	let mut optim = SgdConfig::new().init();
+	let mut optim = AdamConfig::new().init();
 
 	let inputs = Tensor::from_data(
 		TensorData::new(