Files
foxhunt/crates/ml/tests/dqn_rainbow_test.rs
jgrusewski 450c23a6d0 refactor(cuda): eliminate all CPU fallbacks — CUDA mandatory across ML stack
- Remove ALL #[cfg(feature = "cuda")] guards (~400+ occurrences)
- Remove ALL #[cfg_attr(not(feature = "cuda"), ignore)] test annotations (~250)
- Make cuda default feature in 9 ML crates (ml, ml-core, ml-dqn, ml-ppo, etc.)
- Convert nvrtc JIT compilation to precompiled nvcc (searchsorted, prefix_sum)
- Move compile_ptx_for_device() to ml-core for shared access
- Delete dead CPU code: multi_step.rs, self_supervised_pretraining.rs,
  training_guard_gpu_tests.rs, CPU PER buffer paths, CPU Q-diagnostics
- Replace unwrap_or(Device::Cpu) with hard errors everywhere
- Remove dead is_cuda() else branches in DQN/PPO/hyperopt trainers
- Change config defaults from "cpu" to "cuda" (rainbow, tlob, pipeline)
- Port IQL value network to GPU kernel (5 CUDA entry points)
- Port HER goal relabeling to GPU kernel (warp-per-sample)
- Wire DSR GPU-to-CPU sync in training loop
- cfg!(feature = "cuda") → true in inference_validator

Zero warnings, zero errors across entire workspace.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
2026-03-16 21:01:28 +01:00

456 lines
13 KiB
Rust

#![allow(
clippy::assertions_on_constants,
clippy::assertions_on_result_states,
clippy::clone_on_copy,
clippy::decimal_literal_representation,
clippy::doc_markdown,
clippy::empty_line_after_doc_comments,
clippy::field_reassign_with_default,
clippy::get_unwrap,
clippy::identity_op,
clippy::inconsistent_digit_grouping,
clippy::indexing_slicing,
clippy::integer_division,
clippy::len_zero,
clippy::let_underscore_must_use,
clippy::manual_div_ceil,
clippy::manual_let_else,
clippy::manual_range_contains,
clippy::modulo_arithmetic,
clippy::needless_range_loop,
clippy::non_ascii_literal,
clippy::redundant_clone,
clippy::shadow_reuse,
clippy::shadow_same,
clippy::shadow_unrelated,
clippy::single_match_else,
clippy::str_to_string,
clippy::string_slice,
clippy::tests_outside_test_module,
clippy::too_many_lines,
clippy::unnecessary_wraps,
clippy::unseparated_literal_suffix,
clippy::use_debug,
clippy::useless_vec,
clippy::wildcard_enum_match_arm,
clippy::else_if_without_else,
clippy::expect_used,
clippy::missing_const_for_fn,
clippy::similar_names,
clippy::type_complexity,
clippy::collapsible_else_if,
clippy::doc_lazy_continuation,
clippy::items_after_test_module,
clippy::map_clone,
clippy::multiple_unsafe_ops_per_block,
clippy::unwrap_or_default,
clippy::assign_op_pattern,
clippy::needless_borrow,
clippy::println_empty_string,
clippy::unnecessary_cast,
clippy::used_underscore_binding,
clippy::create_dir,
clippy::implicit_saturating_sub,
clippy::exit,
clippy::expect_fun_call,
clippy::too_many_arguments,
clippy::unnecessary_map_or,
clippy::unwrap_used,
dead_code,
unused_imports,
unused_variables,
clippy::cloned_ref_to_slice_refs,
clippy::neg_multiply,
clippy::while_let_loop,
clippy::bool_assert_comparison,
clippy::excessive_precision,
clippy::trivially_copy_pass_by_ref,
clippy::op_ref,
clippy::redundant_closure,
clippy::unnecessary_lazy_evaluations,
clippy::if_then_some_else_none,
clippy::unnecessary_to_owned,
clippy::single_component_path_imports,
)]
//! Rainbow DQN Tests
//!
//! Tests for Rainbow DQN types:
//! - RainbowAgentConfig from rainbow_config.rs
//! - RainbowAgentMetrics from rainbow_config.rs (8 fields)
#![allow(unused_crate_dependencies)]
use ml::dqn::{RainbowAgentConfig, RainbowAgentMetrics};
/// Test: Basic Rainbow agent configuration creation
#[test]
fn test_rainbow_config_creation() {
let config = RainbowAgentConfig::default();
// Verify default values exist and are reasonable
assert!(config.learning_rate > 0.0);
assert!(config.gamma > 0.0 && config.gamma <= 1.0);
assert!(config.batch_size > 0);
assert!(config.replay_buffer_size > 0);
assert!(config.min_replay_size > 0);
assert!(config.target_update_freq > 0);
}
/// Test: Rainbow agent metrics structure
#[test]
fn test_rainbow_metrics_structure() {
let metrics = RainbowAgentMetrics {
total_steps: 100,
replay_buffer_size: 5000,
exploration_rate: 0.5,
current_loss: 0.25,
..Default::default()
};
assert_eq!(metrics.total_steps, 100);
assert_eq!(metrics.replay_buffer_size, 5000);
assert_eq!(metrics.exploration_rate, 0.5);
assert_eq!(metrics.current_loss, 0.25);
}
/// Test: Config validation - learning rate bounds
#[test]
fn test_config_learning_rate_validation() {
let mut config = RainbowAgentConfig::default();
config.learning_rate = 0.001;
assert!(config.learning_rate > 0.0);
config.learning_rate = 0.1;
assert!(config.learning_rate > 0.0);
}
/// Test: Config validation - gamma bounds
#[test]
fn test_config_gamma_validation() {
let mut config = RainbowAgentConfig::default();
config.gamma = 0.99;
assert!(config.gamma > 0.0 && config.gamma <= 1.0);
config.gamma = 0.95;
assert!(config.gamma > 0.0 && config.gamma <= 1.0);
}
/// Test: Config validation - batch size
#[test]
fn test_config_batch_size_validation() {
let mut config = RainbowAgentConfig::default();
config.batch_size = 32;
assert!(config.batch_size > 0);
config.batch_size = 64;
assert!(config.batch_size > 0);
}
/// Test: Config validation - replay buffer size
#[test]
fn test_config_replay_buffer_size() {
let config = RainbowAgentConfig::default();
// Replay buffer should be larger than min replay size
assert!(config.replay_buffer_size >= config.min_replay_size);
// Replay buffer should be larger than batch size
assert!(config.replay_buffer_size >= config.batch_size);
}
/// Test: Config validation - priority parameters
#[test]
fn test_config_priority_parameters() {
let config = RainbowAgentConfig::default();
// Priority alpha should be in (0, 1]
assert!(config.priority_alpha > 0.0 && config.priority_alpha <= 1.0);
// Priority beta should be in (0, 1]
assert!(config.priority_beta > 0.0 && config.priority_beta <= 1.0);
// Priority beta increment should be small positive
assert!(config.priority_beta_increment > 0.0);
assert!(config.priority_beta_increment < 0.01);
}
/// Test: Config validation - update frequencies
#[test]
fn test_config_update_frequencies() {
let config = RainbowAgentConfig::default();
assert!(config.target_update_freq > 0);
assert!(config.train_freq > 0);
assert!(config.noise_reset_freq > 0);
}
/// Test: Metrics with realistic training values
#[test]
fn test_metrics_realistic_values() {
let metrics = RainbowAgentMetrics {
total_steps: 100000,
replay_buffer_size: 50000,
exploration_rate: 0.15,
current_loss: 0.25,
..Default::default()
};
assert_eq!(metrics.total_steps, 100000);
assert_eq!(metrics.replay_buffer_size, 50000);
assert_eq!(metrics.exploration_rate, 0.15);
assert_eq!(metrics.current_loss, 0.25);
}
/// Test: Config clone functionality
#[test]
fn test_config_clone() {
let config = RainbowAgentConfig::default();
let cloned = config.clone();
assert_eq!(cloned.learning_rate, config.learning_rate);
assert_eq!(cloned.gamma, config.gamma);
assert_eq!(cloned.batch_size, config.batch_size);
assert_eq!(cloned.replay_buffer_size, config.replay_buffer_size);
}
/// Test: Config serialize/deserialize compatibility
#[test]
fn test_config_serialization() {
let config = RainbowAgentConfig::default();
let json = serde_json::to_string(&config);
assert!(json.is_ok());
if let Ok(json_str) = json {
let deserialized: Result<RainbowAgentConfig, _> = serde_json::from_str(&json_str);
assert!(deserialized.is_ok());
if let Ok(c) = deserialized {
assert_eq!(c.learning_rate, config.learning_rate);
assert_eq!(c.gamma, config.gamma);
}
}
}
/// Test: Config with custom values
#[test]
fn test_config_custom_values() {
let mut config = RainbowAgentConfig::default();
config.device = "cuda".to_string();
config.min_replay_size = 5000;
config.replay_buffer_size = 50000;
config.batch_size = 64;
config.learning_rate = 0.0005;
config.gamma = 0.95;
config.target_update_freq = 2000;
config.train_freq = 8;
config.priority_alpha = 0.7;
config.priority_beta = 0.5;
config.noise_reset_freq = 200;
assert_eq!(config.device, "cuda");
assert_eq!(config.min_replay_size, 5000);
assert_eq!(config.replay_buffer_size, 50000);
assert_eq!(config.batch_size, 64);
assert_eq!(config.learning_rate, 0.0005);
assert_eq!(config.gamma, 0.95);
assert_eq!(config.target_update_freq, 2000);
assert_eq!(config.train_freq, 8);
assert_eq!(config.priority_alpha, 0.7);
assert_eq!(config.priority_beta, 0.5);
assert_eq!(config.noise_reset_freq, 200);
}
/// Test: Exploration rate tracking
#[test]
fn test_exploration_rate_tracking() {
let metrics1 = RainbowAgentMetrics {
exploration_rate: 1.0,
..Default::default()
};
assert_eq!(metrics1.exploration_rate, 1.0);
let metrics2 = RainbowAgentMetrics {
total_steps: 50000,
replay_buffer_size: 50000,
exploration_rate: 0.5,
current_loss: 1.5,
..Default::default()
};
assert_eq!(metrics2.exploration_rate, 0.5);
let metrics3 = RainbowAgentMetrics {
total_steps: 100000,
replay_buffer_size: 100000,
exploration_rate: 0.1,
current_loss: 0.5,
..Default::default()
};
assert_eq!(metrics3.exploration_rate, 0.1);
}
/// Test: Loss tracking over time
#[test]
fn test_loss_tracking() {
let early_metrics = RainbowAgentMetrics {
total_steps: 1000,
replay_buffer_size: 1000,
exploration_rate: 0.9,
current_loss: 5.0,
..Default::default()
};
assert_eq!(early_metrics.current_loss, 5.0);
let mid_metrics = RainbowAgentMetrics {
total_steps: 50000,
replay_buffer_size: 50000,
exploration_rate: 0.5,
current_loss: 1.0,
..Default::default()
};
assert_eq!(mid_metrics.current_loss, 1.0);
let late_metrics = RainbowAgentMetrics {
total_steps: 100000,
replay_buffer_size: 100000,
exploration_rate: 0.1,
current_loss: 0.1,
..Default::default()
};
assert_eq!(late_metrics.current_loss, 0.1);
}
/// Test: Replay buffer size tracking
#[test]
fn test_replay_buffer_tracking() {
let config = RainbowAgentConfig::default();
let metrics = RainbowAgentMetrics {
total_steps: 10000,
replay_buffer_size: config.replay_buffer_size,
exploration_rate: 0.5,
current_loss: 0.25,
..Default::default()
};
assert_eq!(metrics.replay_buffer_size, config.replay_buffer_size);
}
/// Test: Device configuration
#[test]
fn test_device_configuration() {
let mut config = RainbowAgentConfig::default();
assert_eq!(config.device, "cpu");
config.device = "cuda".to_string();
assert_eq!(config.device, "cuda");
config.device = "cuda:0".to_string();
assert_eq!(config.device, "cuda:0");
}
/// Test: Config network settings
#[test]
fn test_config_network_settings() {
let config = RainbowAgentConfig::default();
let _ = &config.network_config;
}
/// Test: Metrics with zero values
#[test]
fn test_metrics_zero_values() {
let metrics = RainbowAgentMetrics {
total_steps: 0,
replay_buffer_size: 0,
exploration_rate: 0.0,
current_loss: 0.0,
..Default::default()
};
assert_eq!(metrics.total_steps, 0);
assert_eq!(metrics.replay_buffer_size, 0);
assert_eq!(metrics.exploration_rate, 0.0);
assert_eq!(metrics.current_loss, 0.0);
}
/// Test: Metrics with max values
#[test]
fn test_metrics_max_values() {
let metrics = RainbowAgentMetrics {
total_steps: u64::MAX,
replay_buffer_size: 1000000,
exploration_rate: 1.0,
current_loss: 100.0,
..Default::default()
};
assert_eq!(metrics.total_steps, u64::MAX);
assert_eq!(metrics.replay_buffer_size, 1000000);
assert_eq!(metrics.exploration_rate, 1.0);
assert_eq!(metrics.current_loss, 100.0);
}
/// Test: Training progress simulation
#[test]
fn test_training_progress_simulation() {
// Early training
let early = RainbowAgentMetrics {
total_steps: 100,
replay_buffer_size: 100,
exploration_rate: 0.99,
current_loss: 10.0,
..Default::default()
};
// Mid training
let mid = RainbowAgentMetrics {
total_steps: 50000,
replay_buffer_size: 50000,
exploration_rate: 0.5,
current_loss: 2.0,
..Default::default()
};
// Late training
let late = RainbowAgentMetrics {
total_steps: 100000,
replay_buffer_size: 100000,
exploration_rate: 0.05,
current_loss: 0.5,
..Default::default()
};
// Verify progression
assert!(early.exploration_rate > mid.exploration_rate);
assert!(mid.exploration_rate > late.exploration_rate);
assert!(early.current_loss > mid.current_loss);
assert!(mid.current_loss > late.current_loss);
}
/// Test: Config default device is CPU
#[test]
fn test_config_default_device() {
let config = RainbowAgentConfig::default();
assert_eq!(config.device, "cpu");
}
/// Test: Config default learning rate is reasonable
#[test]
fn test_config_default_learning_rate() {
let config = RainbowAgentConfig::default();
assert!(config.learning_rate > 0.0);
assert!(config.learning_rate < 0.01); // Reasonable upper bound for DQN
}
/// Test: Config default gamma is reasonable
#[test]
fn test_config_default_gamma() {
let config = RainbowAgentConfig::default();
assert!(config.gamma > 0.9); // Should be high for RL
assert!(config.gamma <= 1.0);
}