remove redundant comments

Cargo.lock

@@ -1080,6 +1080,15 @@ dependencies = [
  "rand_core 0.10.0",
 ]
 
+[[package]]
+name = "chrono"
+version = "0.4.44"
+source = "registry+https://github.com/rust-lang/crates.io-index"
+checksum = "c673075a2e0e5f4a1dde27ce9dee1ea4558c7ffe648f576438a20ca1d2acc4b0"
+dependencies = [
+ "num-traits",
+]
+
 [[package]]
 name = "cipher"
 version = "0.4.4"
@@ -1109,7 +1118,7 @@ checksum = "fe6d2e5af09e8c8ad56c969f2157a3d4238cebc7c55f0a517728c38f7b200f81"
 dependencies = [
  "serde",
  "termcolor",
- "unicode-width 0.2.0",
+ "unicode-width 0.1.14",
 ]
 
 [[package]]
@@ -1120,7 +1129,7 @@ checksum = "af491d569909a7e4dee0ad7db7f5341fef5c614d5b8ec8cf765732aba3cff681"
 dependencies = [
  "serde",
  "termcolor",
- "unicode-width 0.2.0",
+ "unicode-width 0.1.14",
 ]
 
 [[package]]
@@ -1135,7 +1144,7 @@ version = "3.1.1"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "faf9468729b8cbcea668e36183cb69d317348c2e08e994829fb56ebfdfbaac34"
 dependencies = [
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -2232,7 +2241,7 @@ source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "39cab71617ae0d63f51a36d69f866391735b51691dbda63cf6f96d042b63efeb"
 dependencies = [
  "libc",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -2919,7 +2928,7 @@ dependencies = [
  "log",
  "presser",
  "thiserror 2.0.18",
- "windows 0.61.3",
+ "windows 0.58.0",
 ]
 
 [[package]]
@@ -5054,7 +5063,7 @@ dependencies = [
  "errno",
  "libc",
  "linux-raw-sys 0.12.1",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -5451,7 +5460,8 @@ name = "strafe-ai"
 version = "0.1.0"
 dependencies = [
  "burn",
- "png",
+ "chrono",
+ "glam",
  "pollster",
  "strafesnet_common",
  "strafesnet_graphics",
@@ -5479,9 +5489,9 @@ 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",
@@ -5516,9 +5526,9 @@ 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",
@@ -5730,7 +5740,7 @@ dependencies = [
  "getrandom 0.4.2",
  "once_cell",
  "rustix 1.1.4",
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]
@@ -6989,7 +6999,7 @@ version = "0.1.11"
 source = "registry+https://github.com/rust-lang/crates.io-index"
 checksum = "c2a7b1c03c876122aa43f3020e6c3c3ee5c05081c9a00739faf7503aeba10d22"
 dependencies = [
- "windows-sys 0.59.0",
+ "windows-sys 0.52.0",
 ]
 
 [[package]]

Cargo.toml

@@ -5,13 +5,14 @@ edition = "2024"
 
 [dependencies]
 burn = { version = "0.20.1", features = ["cuda", "autodiff"] }
+glam = "0.32.1"
+pollster = "0.4.0"
 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"
-png = "0.18.1"
+chrono = { version = "0.4.44", default-features = false, features = ["now"] }

src/main.rs

@@ -1,43 +1,21 @@
 use burn::backend::Autodiff;
 use burn::nn::loss::{MseLoss, Reduction};
-use burn::nn::{Linear, LinearConfig, Relu};
-use burn::optim::{GradientsParams, Optimizer, SgdConfig};
+use burn::nn::{Dropout, DropoutConfig, Linear, LinearConfig, Relu};
+use burn::optim::{AdamConfig, GradientsParams, Optimizer};
 use burn::prelude::*;
 
 type InferenceBackend = burn::backend::Cuda<f32>;
 type TrainingBackend = Autodiff<InferenceBackend>;
 
 const LIMITS: wgpu::Limits = wgpu::Limits::defaults();
+const FORMAT: wgpu::TextureFormat = wgpu::TextureFormat::Rgba8UnormSrgb;
 use strafesnet_graphics::setup;
 use strafesnet_roblox_bot_file::v0;
 
-pub fn output_image_native(image_data: &[u8], texture_dims: (usize, usize), path: String) {
-	use std::io::Write;
-
-	let mut png_data = Vec::<u8>::with_capacity(image_data.len());
-	let mut encoder =
-		png::Encoder::new(&mut png_data, texture_dims.0 as u32, texture_dims.1 as u32);
-	encoder.set_color(png::ColorType::Grayscale);
-	let mut png_writer = encoder.write_header().unwrap();
-	png_writer.write_image_data(image_data).unwrap();
-	png_writer.finish().unwrap();
-
-	let mut file = std::fs::File::create(&path).unwrap();
-	file.write_all(&png_data).unwrap();
-}
-
-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,
-	INPUT >> 3,
-	INPUT >> 4,
-	INPUT >> 5,
-	INPUT >> 6,
-	INPUT >> 7,
-];
+const SIZE: glam::UVec2 = glam::uvec2(64, 36);
+const POSITION_HISTORY: usize = 4;
+const INPUT: usize = (SIZE.x * SIZE.y) as usize + POSITION_HISTORY * 3;
+const HIDDEN: [usize; 2] = [INPUT >> 3, INPUT >> 7];
 // MoveForward
 // MoveLeft
 // MoveBack
@@ -47,9 +25,13 @@ const HIDDEN: [usize; 7] = [
 // mouse_dy
 const OUTPUT: usize = 7;
 
+// bytes_per_row needs to be a multiple of 256.
+const STRIDE_SIZE: u32 = (SIZE.x * size_of::<f32>() as u32).next_multiple_of(256);
+
 #[derive(Module, Debug)]
 struct Net<B: Backend> {
 	input: Linear<B>,
+	dropout: Dropout,
 	hidden: [Linear<B>; HIDDEN.len() - 1],
 	output: Linear<B>,
 	activation: Relu,
@@ -66,8 +48,10 @@ impl<B: Backend> Net<B> {
 			layer
 		});
 		let output = LinearConfig::new(last_size, OUTPUT).init(device);
+		let dropout = DropoutConfig::new(0.1).init();
 		Self {
 			input,
+			dropout,
 			hidden,
 			output,
 			activation: Relu::new(),
@@ -75,6 +59,7 @@ impl<B: Backend> Net<B> {
 	}
 	fn forward(&self, input: Tensor<B, 2>) -> Tensor<B, 2> {
 		let x = self.input.forward(input);
+		let x = self.dropout.forward(x);
 		let mut x = self.activation.forward(x);
 		for layer in &self.hidden {
 			x = layer.forward(x);
@@ -84,6 +69,164 @@ impl<B: Backend> Net<B> {
 	}
 }
 
+struct GraphicsState {
+	device: wgpu::Device,
+	queue: wgpu::Queue,
+	graphics: strafesnet_roblox_bot_player::graphics::Graphics,
+	graphics_texture_view: wgpu::TextureView,
+	output_staging_buffer: wgpu::Buffer,
+	texture_data: Vec<u8>,
+	position_history: Vec<glam::Vec3>,
+}
+impl GraphicsState {
+	fn new(map: &strafesnet_common::map::CompleteMap) -> Self {
+		let desc = wgpu::InstanceDescriptor::new_without_display_handle_from_env();
+		let instance = wgpu::Instance::new(desc);
+		let (device, queue) = pollster::block_on(async {
+			let adapter = instance
+				.request_adapter(&wgpu::RequestAdapterOptions {
+					power_preference: wgpu::PowerPreference::HighPerformance,
+					force_fallback_adapter: false,
+					compatible_surface: None,
+				})
+				.await
+				.unwrap();
+			setup::step4::request_device(&adapter, LIMITS)
+				.await
+				.unwrap()
+		});
+		let mut graphics = strafesnet_roblox_bot_player::graphics::Graphics::new(
+			&device, &queue, SIZE, FORMAT, LIMITS,
+		);
+		graphics.change_map(&device, &queue, map).unwrap();
+		let graphics_texture = device.create_texture(&wgpu::TextureDescriptor {
+			label: Some("RGB texture"),
+			format: FORMAT,
+			size: wgpu::Extent3d {
+				width: SIZE.x,
+				height: SIZE.y,
+				depth_or_array_layers: 1,
+			},
+			mip_level_count: 1,
+			sample_count: 1,
+			dimension: wgpu::TextureDimension::D2,
+			usage: wgpu::TextureUsages::RENDER_ATTACHMENT | wgpu::TextureUsages::TEXTURE_BINDING,
+			view_formats: &[],
+		});
+		let graphics_texture_view = graphics_texture.create_view(&wgpu::TextureViewDescriptor {
+			label: Some("RGB texture view"),
+			aspect: wgpu::TextureAspect::All,
+			usage: Some(
+				wgpu::TextureUsages::RENDER_ATTACHMENT | wgpu::TextureUsages::TEXTURE_BINDING,
+			),
+			..Default::default()
+		});
+		let texture_data = Vec::<u8>::with_capacity((STRIDE_SIZE * SIZE.y) as usize);
+		let output_staging_buffer = device.create_buffer(&wgpu::BufferDescriptor {
+			label: Some("Output staging buffer"),
+			size: texture_data.capacity() as u64,
+			usage: wgpu::BufferUsages::COPY_DST | wgpu::BufferUsages::MAP_READ,
+			mapped_at_creation: false,
+		});
+		let position_history = Vec::with_capacity(POSITION_HISTORY);
+		Self {
+			device,
+			queue,
+			graphics,
+			graphics_texture_view,
+			output_staging_buffer,
+			texture_data,
+			position_history,
+		}
+	}
+	fn generate_inputs(&mut self, pos: glam::Vec3, angles: glam::Vec2, inputs: &mut Vec<f32>) {
+		// write position history to model inputs
+		if !self.position_history.is_empty() {
+			let camera = strafesnet_graphics::graphics::view_inv(pos, angles).inverse();
+			for &pos in self.position_history.iter().rev() {
+				let relative_pos = camera.transform_vector3(pos);
+				inputs.extend_from_slice(&relative_pos.to_array());
+			}
+		}
+		// fill remaining history with zeroes
+		for _ in self.position_history.len()..POSITION_HISTORY {
+			inputs.extend_from_slice(&[0.0, 0.0, 0.0]);
+		}
+
+		// track position history
+		if self.position_history.len() < POSITION_HISTORY {
+			self.position_history.push(pos);
+		} else {
+			self.position_history.rotate_left(1);
+			*self.position_history.last_mut().unwrap() = pos;
+		}
+
+		let mut encoder = self
+			.device
+			.create_command_encoder(&wgpu::CommandEncoderDescriptor {
+				label: Some("wgpu encoder"),
+			});
+
+		// render!
+		self.graphics
+			.encode_commands(&mut encoder, &self.graphics_texture_view, pos, angles);
+
+		// copy the depth texture into ram
+		encoder.copy_texture_to_buffer(
+			wgpu::TexelCopyTextureInfo {
+				texture: self.graphics.depth_texture(),
+				mip_level: 0,
+				origin: wgpu::Origin3d::ZERO,
+				aspect: wgpu::TextureAspect::All,
+			},
+			wgpu::TexelCopyBufferInfo {
+				buffer: &self.output_staging_buffer,
+				layout: wgpu::TexelCopyBufferLayout {
+					offset: 0,
+					// This needs to be a multiple of 256.
+					bytes_per_row: Some(STRIDE_SIZE),
+					rows_per_image: Some(SIZE.y),
+				},
+			},
+			wgpu::Extent3d {
+				width: SIZE.x,
+				height: SIZE.y,
+				depth_or_array_layers: 1,
+			},
+		);
+
+		self.queue.submit([encoder.finish()]);
+
+		// map buffer
+		let buffer_slice = self.output_staging_buffer.slice(..);
+		let (sender, receiver) = std::sync::mpsc::channel();
+		buffer_slice.map_async(wgpu::MapMode::Read, move |r| sender.send(r).unwrap());
+		self.device
+			.poll(wgpu::PollType::wait_indefinitely())
+			.unwrap();
+		receiver.recv().unwrap().unwrap();
+
+		// copy texture inside a scope so the mapped view gets dropped
+		{
+			let view = buffer_slice.get_mapped_range();
+			self.texture_data.extend_from_slice(&view[..]);
+		}
+		self.output_staging_buffer.unmap();
+
+		// discombolulate stride
+		for y in 0..SIZE.y {
+			inputs.extend(
+				self.texture_data[(STRIDE_SIZE * y) as usize
+					..(STRIDE_SIZE * y + SIZE.x * size_of::<f32>() as u32) as usize]
+					.chunks_exact(4)
+					.map(|b| 1.0 - 2.0 * f32::from_le_bytes(b.try_into().unwrap())),
+			)
+		}
+
+		self.texture_data.clear();
+	}
+}
+
 fn training() {
 	let gpu_id: usize = std::env::args()
 		.skip(1)
@@ -108,70 +251,16 @@ fn training() {
 	let world_offset = bot.world_offset();
 	let timelines = bot.timelines();
 
-	// setup graphics
-	let desc = wgpu::InstanceDescriptor::new_without_display_handle_from_env();
-	let instance = wgpu::Instance::new(desc);
-	let (device, queue) = pollster::block_on(async {
-		let adapter = instance
-			.request_adapter(&wgpu::RequestAdapterOptions {
-				power_preference: wgpu::PowerPreference::HighPerformance,
-				force_fallback_adapter: false,
-				compatible_surface: None,
-			})
-			.await
-			.unwrap();
-		setup::step4::request_device(&adapter, LIMITS)
-			.await
-			.unwrap()
-	});
-
-	const FORMAT: wgpu::TextureFormat = wgpu::TextureFormat::Rgba8UnormSrgb;
-	let size = [SIZE_X as u32, SIZE_Y as u32].into();
-	let mut graphics = strafesnet_roblox_bot_player::graphics::Graphics::new(
-		&device, &queue, size, FORMAT, LIMITS,
-	);
-	graphics.change_map(&device, &queue, &map).unwrap();
-
 	// setup simulation
 	// run progressively longer segments of the map, starting very close to the end of the run and working the starting time backwards until the ai can run the whole map
 
-	// set up textures
-	let graphics_texture = device.create_texture(&wgpu::TextureDescriptor {
-		label: Some("RGB texture"),
-		format: FORMAT,
-		size: wgpu::Extent3d {
-			width: size.x,
-			height: size.y,
-			depth_or_array_layers: 1,
-		},
-		mip_level_count: 1,
-		sample_count: 1,
-		dimension: wgpu::TextureDimension::D2,
-		usage: wgpu::TextureUsages::RENDER_ATTACHMENT
-			| wgpu::TextureUsages::TEXTURE_BINDING
-			| wgpu::TextureUsages::COPY_SRC,
-		view_formats: &[],
-	});
-	let graphics_texture_view = graphics_texture.create_view(&wgpu::TextureViewDescriptor {
-		label: Some("RGB texture view"),
-		aspect: wgpu::TextureAspect::All,
-		usage: Some(wgpu::TextureUsages::RENDER_ATTACHMENT | wgpu::TextureUsages::TEXTURE_BINDING),
-		..Default::default()
-	});
-	// bytes_per_row needs to be a multiple of 256.
-	let stride_size = (size.x * size_of::<f32>() as u32).next_multiple_of(256);
-	let mut texture_data = Vec::<u8>::with_capacity((stride_size * size.y) as usize);
-	let output_staging_buffer = device.create_buffer(&wgpu::BufferDescriptor {
-		label: Some("Output staging buffer"),
-		size: texture_data.capacity() as u64,
-		usage: wgpu::BufferUsages::COPY_DST | wgpu::BufferUsages::MAP_READ,
-		mapped_at_creation: false,
-	});
+	// set up graphics
+	let mut g = GraphicsState::new(&map);
 
 	// training data
 	let training_samples = timelines.input_events.len() - 1;
 
-	let input_size = (size.x * size.y) as usize * size_of::<f32>();
+	let input_size = INPUT * size_of::<f32>();
 	let mut inputs = Vec::with_capacity(input_size * training_samples);
 	let mut targets = Vec::with_capacity(OUTPUT * training_samples);
 
@@ -184,7 +273,7 @@ fn training() {
 	let mut last_mx = first.event.mouse_pos.x;
 	let mut last_my = first.event.mouse_pos.y;
 
-	for (i, input_event) in it.enumerate() {
+	for input_event in it {
 		let mouse_dx = input_event.event.mouse_pos.x - last_mx;
 		let mouse_dy = input_event.event.mouse_pos.y - last_my;
 		last_mx = input_event.event.mouse_pos.x;
@@ -249,92 +338,17 @@ fn training() {
 				.unwrap(),
 		};
 
-		fn p(v: v0::Vector3) -> [f32; 3] {
-			[v.x, v.y, v.z]
+		fn vec3(v: v0::Vector3) -> glam::Vec3 {
+			glam::vec3(v.x, v.y, v.z)
 		}
-		fn a(a: v0::Vector3) -> [f32; 2] {
-			[a.y, a.x]
-		}
-		fn add<T: core::ops::Add>(lhs: T, rhs: T) -> T::Output {
-			lhs + rhs
+		fn angles(a: v0::Vector3) -> glam::Vec2 {
+			glam::vec2(a.y, a.x)
 		}
 
-		let mut encoder = device.create_command_encoder(&wgpu::CommandEncoderDescriptor {
-			label: Some("wgpu encoder"),
-		});
+		let pos = vec3(output_event.event.position) - world_offset;
+		let angles = angles(output_event.event.angles);
 
-		// render!
-		graphics.encode_commands(
-			&mut encoder,
-			&graphics_texture_view,
-			add(world_offset, p(output_event.event.position).into()),
-			a(output_event.event.angles).into(),
-		);
-
-		// copy the depth texture into ram
-		encoder.copy_texture_to_buffer(
-			wgpu::TexelCopyTextureInfo {
-				texture: &graphics_texture,
-				mip_level: 0,
-				origin: wgpu::Origin3d::ZERO,
-				aspect: wgpu::TextureAspect::All,
-			},
-			wgpu::TexelCopyBufferInfo {
-				buffer: &output_staging_buffer,
-				layout: wgpu::TexelCopyBufferLayout {
-					offset: 0,
-					// This needs to be a multiple of 256.
-					bytes_per_row: Some(stride_size as u32),
-					rows_per_image: None,
-				},
-			},
-			wgpu::Extent3d {
-				width: size.x,
-				height: size.y,
-				depth_or_array_layers: 1,
-			},
-		);
-
-		queue.submit([encoder.finish()]);
-
-		// map buffer
-		let buffer_slice = output_staging_buffer.slice(..);
-		let (sender, receiver) = std::sync::mpsc::channel();
-		buffer_slice.map_async(wgpu::MapMode::Read, move |r| sender.send(r).unwrap());
-		device.poll(wgpu::PollType::wait_indefinitely()).unwrap();
-		receiver.recv().unwrap().unwrap();
-
-		// copy texture inside a scope so the mapped view gets dropped
-		{
-			let view = buffer_slice.get_mapped_range();
-			texture_data.extend_from_slice(&view[..]);
-		}
-		output_staging_buffer.unmap();
-
-		println!("{texture_data:?}");
-
-		// discombolulate stride
-		for y in 0..size.y {
-			inputs.extend(
-				texture_data[(stride_size * y) as usize
-					..(stride_size * y + size.x * size_of::<f32>() as u32) as usize]
-					.chunks_exact(4)
-					.map(|b| b[0] as f32 + b[1] as f32 + b[2] as f32),
-			)
-		}
-
-		// write a png
-		output_image_native(
-			&inputs[i * INPUT..(i + 1) * INPUT]
-				.iter()
-				.copied()
-				.map(|f| f as u8)
-				.collect::<Vec<u8>>(),
-			(SIZE_X, SIZE_Y),
-			format!("depth_images/{i}.png").into(),
-		);
-
-		texture_data.clear();
+		g.generate_inputs(pos, angles, &mut inputs);
 	}
 
 	let device = burn::backend::cuda::CudaDevice::new(gpu_id);
@@ -342,13 +356,10 @@ 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(
-			inputs,
-			Shape::new([training_samples, (size.x * size.y) as usize]),
-		),
+		TensorData::new(inputs, Shape::new([training_samples, INPUT])),
 		&device,
 	);
 	let targets = Tensor::from_data(
@@ -356,8 +367,11 @@ fn training() {
 		&device,
 	);
 
-	const LEARNING_RATE: f64 = 0.5;
-	const EPOCHS: usize = 10000;
+	const LEARNING_RATE: f64 = 0.001;
+	const EPOCHS: usize = 100000;
+
+	let mut best_model = model.clone();
+	let mut best_loss = f32::INFINITY;
 
 	for epoch in 0..EPOCHS {
 		let predictions = model.forward(inputs.clone());
@@ -374,6 +388,12 @@ fn training() {
 		let grads = loss.backward();
 		let grads = GradientsParams::from_grads(grads, &model);
 
+		// get the best model
+		if loss_scalar < best_loss {
+			best_loss = loss_scalar;
+			best_model = model.clone();
+		}
+
 		model = optim.step(LEARNING_RATE, model, grads);
 
 		if epoch % (EPOCHS >> 4) == 0 || epoch == EPOCHS - 1 {
@@ -381,15 +401,211 @@ fn training() {
 			println!("  epoch {:>5} | loss = {:.8}", epoch, loss_scalar);
 		}
 	}
+
+	let date_string = format!("{}_{}.model", chrono::Utc::now(), best_loss);
+	best_model
+		.save_file(
+			date_string,
+			&burn::record::BinFileRecorder::<burn::record::FullPrecisionSettings>::new(),
+		)
+		.unwrap();
+}
+
+use strafesnet_common::instruction::TimedInstruction;
+use strafesnet_common::mouse::MouseState;
+use strafesnet_common::physics::{
+	Instruction as PhysicsInputInstruction, MiscInstruction, ModeInstruction, MouseInstruction,
+	SetControlInstruction, Time as PhysicsTime,
+};
+use strafesnet_physics::physics::{PhysicsContext, PhysicsData, PhysicsState};
+
+pub struct Recording {
+	instructions: Vec<TimedInstruction<PhysicsInputInstruction, PhysicsTime>>,
+}
+struct FrameState {
+	trajectory: strafesnet_physics::physics::Trajectory,
+	camera: strafesnet_physics::physics::PhysicsCamera,
+}
+impl FrameState {
+	fn pos(&self, time: PhysicsTime) -> glam::Vec3 {
+		self.trajectory
+			.extrapolated_position(time)
+			.map(Into::<f32>::into)
+			.to_array()
+			.into()
+	}
+	fn angles(&self) -> glam::Vec2 {
+		self.camera.simulate_move_angles(glam::IVec2::ZERO)
+	}
+}
+struct Session {
+	geometry_shared: PhysicsData,
+	simulation: PhysicsState,
+	recording: Recording,
+}
+impl Session {
+	fn get_frame_state(&self) -> FrameState {
+		FrameState {
+			trajectory: self.simulation.camera_trajectory(&self.geometry_shared),
+			camera: self.simulation.camera(),
+		}
+	}
+	fn run(&mut self, time: PhysicsTime, instruction: PhysicsInputInstruction) {
+		let instruction = TimedInstruction { time, instruction };
+		self.recording.instructions.push(instruction.clone());
+		PhysicsContext::run_input_instruction(
+			&mut self.simulation,
+			&self.geometry_shared,
+			instruction,
+		);
+	}
 }
 
 fn inference() {
+	let mut args = std::env::args().skip(1);
+
+	// pick device
+	let gpu_id: usize = args
+		.next()
+		.map(|id| id.parse().unwrap())
+		.unwrap_or_default();
+	let device = burn::backend::cuda::CudaDevice::new(gpu_id);
+
+	// load model
+	let path: std::path::PathBuf = args.next().unwrap().parse().unwrap();
+	let mut model: Net<InferenceBackend> = Net::init(&device);
+	model = model
+		.load_file(
+			path,
+			&burn::record::BinFileRecorder::<burn::record::FullPrecisionSettings>::new(),
+			&device,
+		)
+		.unwrap();
+
 	// load map
+	let map_file = include_bytes!("../files/bhop_marble_5692093612.snfm");
+	let map = strafesnet_snf::read_map(std::io::Cursor::new(map_file))
+		.unwrap()
+		.into_complete_map()
+		.unwrap();
+	let modes = map.modes.clone().denormalize();
+	let mode = modes
+		.get_mode(strafesnet_common::gameplay_modes::ModeId::MAIN)
+		.unwrap();
+	let start_zone = map.models.get(mode.get_start().get() as usize).unwrap();
+	let start_offset = glam::Vec3::from_array(
+		start_zone
+			.transform
+			.translation
+			.map(|f| f.into())
+			.to_array(),
+	);
+
+	// setup graphics
+	let mut g = GraphicsState::new(&map);
+
 	// setup simulation
+	let mut session = Session {
+		geometry_shared: PhysicsData::new(&map),
+		simulation: PhysicsState::default(),
+		recording: Recording {
+			instructions: Vec::new(),
+		},
+	};
+
+	let mut time = PhysicsTime::ZERO;
+
+	// reset to start zone
+	session.run(time, PhysicsInputInstruction::Mode(ModeInstruction::Reset));
+	// session.run(
+	// 	time,
+	// 	PhysicsInputInstruction::Misc(MiscInstruction::SetSensitivity(?)),
+	// );
+	session.run(
+		time,
+		PhysicsInputInstruction::Mode(ModeInstruction::Restart(
+			strafesnet_common::gameplay_modes::ModeId::MAIN,
+		)),
+	);
+
+	// TEMP: turn mouse left
+	let mut mouse_pos = glam::ivec2(-5300, 0);
+
+	const STEP: PhysicsTime = PhysicsTime::from_millis(10);
+	let mut input_floats = Vec::new();
 	// setup agent-simulation feedback loop
-	// go!
+	for _ in 0..20 * 100 {
+		// generate inputs
+		let frame_state = session.get_frame_state();
+		g.generate_inputs(
+			frame_state.pos(time) - start_offset,
+			frame_state.angles(),
+			&mut input_floats,
+		);
+
+		// inference
+		let inputs = Tensor::from_data(
+			TensorData::new(input_floats.clone(), Shape::new([1, INPUT])),
+			&device,
+		);
+		let outputs = model.forward(inputs).into_data().into_vec::<f32>().unwrap();
+
+		let &[
+			move_forward,
+			move_left,
+			move_back,
+			move_right,
+			jump,
+			mouse_dx,
+			mouse_dy,
+		] = outputs.as_slice()
+		else {
+			panic!()
+		};
+
+		macro_rules! set_control {
+			($control:ident,$output:expr) => {
+				session.run(
+					time,
+					PhysicsInputInstruction::SetControl(SetControlInstruction::$control(
+						0.5 < $output,
+					)),
+				);
+			};
+		}
+		set_control!(SetMoveForward, move_forward);
+		set_control!(SetMoveLeft, move_left);
+		set_control!(SetMoveBack, move_back);
+		set_control!(SetMoveRight, move_right);
+		set_control!(SetJump, jump);
+
+		mouse_pos += glam::vec2(mouse_dx, mouse_dy).round().as_ivec2();
+		let next_time = time + STEP;
+		session.run(
+			time,
+			PhysicsInputInstruction::Mouse(MouseInstruction::SetNextMouse(MouseState {
+				pos: mouse_pos,
+				time: next_time,
+			})),
+		);
+
+		time = next_time;
+
+		// clear
+		input_floats.clear();
+	}
+
+	let date_string = format!("{}.snfb", chrono::Utc::now());
+	let file = std::fs::File::create(date_string).unwrap();
+	strafesnet_snf::bot::write_bot(
+		std::io::BufWriter::new(file),
+		strafesnet_physics::VERSION.get(),
+		core::mem::take(&mut session.recording.instructions),
+	)
+	.unwrap();
 }
 
 fn main() {
-	training();
+	// training();
+	inference();
 }