#![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, )] //! Tests for PPO Hidden State Management //! //! Validates LSTM hidden state initialization, propagation, and reset logic. //! All state storage is host-side Vec (no Candle tensors). // candle eliminated -- HiddenStateManager uses host-side Vec use ml::ppo::hidden_state_manager::HiddenStateManager; #[test] fn test_hidden_state_initialization() -> Result<(), Box> { // Test that hidden states are initialized to zeros let num_layers = 2; let batch_size = 4; let hidden_dim = 128; let manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?; let (policy_h, policy_c) = manager.get_policy_state(); let (value_h, value_c) = manager.get_value_state(); // Verify lengths (flat: num_layers * batch_size * hidden_dim) let expected_len = num_layers * batch_size * hidden_dim; assert_eq!(policy_h.len(), expected_len); assert_eq!(policy_c.len(), expected_len); assert_eq!(value_h.len(), expected_len); assert_eq!(value_c.len(), expected_len); // Verify all zeros let policy_h_sum: f32 = policy_h.iter().sum(); let policy_c_sum: f32 = policy_c.iter().sum(); let value_h_sum: f32 = value_h.iter().sum(); let value_c_sum: f32 = value_c.iter().sum(); assert_eq!(policy_h_sum, 0.0, "Policy hidden state should be zeros"); assert_eq!(policy_c_sum, 0.0, "Policy cell state should be zeros"); assert_eq!(value_h_sum, 0.0, "Value hidden state should be zeros"); assert_eq!(value_c_sum, 0.0, "Value cell state should be zeros"); Ok(()) } #[test] fn test_hidden_state_propagation() -> Result<(), Box> { // Test that hidden states carry across timesteps let num_layers = 2; let batch_size = 4; let hidden_dim = 128; let mut manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?; let total = num_layers * batch_size * hidden_dim; // Create new states with non-zero values let new_h = vec![1.0_f32; total]; let new_c = vec![2.0_f32; total]; // c = 2.0 (was affine(2.0, 0.0) on ones) // Update policy states manager.update_policy_state(new_h.clone(), new_c.clone())?; // Verify states were updated let (policy_h, policy_c) = manager.get_policy_state(); let policy_h_sum: f32 = policy_h.iter().sum(); let policy_c_sum: f32 = policy_c.iter().sum(); let expected_h_sum = total as f32; let expected_c_sum = total as f32 * 2.0; assert!( (policy_h_sum - expected_h_sum).abs() < 0.01, "Policy hidden state should be updated. Expected {}, got {}", expected_h_sum, policy_h_sum ); assert!( (policy_c_sum - expected_c_sum).abs() < 0.01, "Policy cell state should be updated. Expected {}, got {}", expected_c_sum, policy_c_sum ); // Update value states manager.update_value_state(new_h, new_c)?; // Verify value states were updated let (value_h, value_c) = manager.get_value_state(); let value_h_sum: f32 = value_h.iter().sum(); let value_c_sum: f32 = value_c.iter().sum(); assert!( (value_h_sum - expected_h_sum).abs() < 0.01, "Value hidden state should be updated. Expected {}, got {}", expected_h_sum, value_h_sum ); assert!( (value_c_sum - expected_c_sum).abs() < 0.01, "Value cell state should be updated. Expected {}, got {}", expected_c_sum, value_c_sum ); Ok(()) } #[test] fn test_hidden_state_reset_on_done() -> Result<(), Box> { // Test that states reset when episodes end let num_layers = 2; let batch_size = 4; let hidden_dim = 128; let mut manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?; let total = num_layers * batch_size * hidden_dim; // Set states to non-zero (all ones) let ones = vec![1.0_f32; total]; manager.update_policy_state(ones.clone(), ones.clone())?; manager.update_value_state(ones.clone(), ones.clone())?; // Create done mask: environments 0 and 2 are done (bool, not u8 tensor) let done_mask = vec![true, false, true, false]; // Reset states for done environments manager.reset_on_done(&done_mask)?; // Verify policy states let (policy_h, policy_c) = manager.get_policy_state(); // Check that environments 0 and 2 are reset (all zeros) // and environments 1 and 3 retain their values (all ones) for layer in 0..num_layers { for env in 0..batch_size { for dim in 0..hidden_dim { let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim; let expected = if env == 0 || env == 2 { 0.0 } else { 1.0 }; assert!( (policy_h[idx] - expected).abs() < 0.01, "Policy hidden state at [{}, {}, {}] should be {}. Got {}", layer, env, dim, expected, policy_h[idx] ); assert!( (policy_c[idx] - expected).abs() < 0.01, "Policy cell state at [{}, {}, {}] should be {}. Got {}", layer, env, dim, expected, policy_c[idx] ); } } } // Verify value states similarly let (value_h, value_c) = manager.get_value_state(); for layer in 0..num_layers { for env in 0..batch_size { for dim in 0..hidden_dim { let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim; let expected = if env == 0 || env == 2 { 0.0 } else { 1.0 }; assert!( (value_h[idx] - expected).abs() < 0.01, "Value hidden state at [{}, {}, {}] should be {}. Got {}", layer, env, dim, expected, value_h[idx] ); assert!( (value_c[idx] - expected).abs() < 0.01, "Value cell state at [{}, {}, {}] should be {}. Got {}", layer, env, dim, expected, value_c[idx] ); } } } Ok(()) } #[test] fn test_hidden_state_batching() -> Result<(), Box> { // Test that manager handles multiple parallel environments correctly let num_layers = 2; let batch_size = 8; // 8 parallel environments let hidden_dim = 64; let mut manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?; // Create different values for different environments let total = num_layers * batch_size * hidden_dim; let mut h_data = vec![0.0_f32; total]; let mut c_data = vec![0.0_f32; total]; for layer in 0..num_layers { for env in 0..batch_size { for dim in 0..hidden_dim { let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim; h_data[idx] = (env + 1) as f32; // Environment 0 = 1.0, env 1 = 2.0, etc. c_data[idx] = (env + 1) as f32 * 10.0; // Environment 0 = 10.0, env 1 = 20.0, etc. } } } // Update states (Vec directly, no Tensor conversion needed) manager.update_policy_state(h_data.clone(), c_data.clone())?; // Verify each environment has correct values let (policy_h, policy_c) = manager.get_policy_state(); for layer in 0..num_layers { for env in 0..batch_size { for dim in 0..hidden_dim { let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim; let expected_h = (env + 1) as f32; let expected_c = (env + 1) as f32 * 10.0; assert!( (policy_h[idx] - expected_h).abs() < 0.01, "Hidden state for env {} should be {}. Got {}", env, expected_h, policy_h[idx] ); assert!( (policy_c[idx] - expected_c).abs() < 0.01, "Cell state for env {} should be {}. Got {}", env, expected_c, policy_c[idx] ); } } } Ok(()) }