Complete Candle→cudarc migration for all test code. The workspace now compiles clean with `cargo check --workspace --tests` (0 errors) and `cargo clippy --workspace --lib -D warnings` (0 errors). Migration patterns applied across all files: - Tensor → GpuTensor (from_host, zeros, randn, full) - Device → MlDevice (cuda, cuda_if_available, new_cuda) - All GpuTensor ops now take &Arc<CudaStream> - VarMap/VarBuilder → GpuVarStore or removed - DType removed (everything f32) - Candle autograd tests (Var, GradStore, backward) → #[ignore] - Preprocessing tests → host-side Vec<f32> (CPU-side by design) - PPO hidden state → host-side Vec<f32> slices - UnifiedTrainable: forward_loss(&[f32], &[f32]) → f64 Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
323 lines
11 KiB
Rust
323 lines
11 KiB
Rust
#![allow(
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clippy::assertions_on_constants,
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clippy::assertions_on_result_states,
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clippy::clone_on_copy,
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clippy::decimal_literal_representation,
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clippy::doc_markdown,
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clippy::empty_line_after_doc_comments,
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clippy::field_reassign_with_default,
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clippy::get_unwrap,
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clippy::identity_op,
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clippy::inconsistent_digit_grouping,
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clippy::indexing_slicing,
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clippy::integer_division,
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clippy::len_zero,
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clippy::let_underscore_must_use,
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clippy::manual_div_ceil,
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clippy::manual_let_else,
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clippy::manual_range_contains,
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clippy::modulo_arithmetic,
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clippy::needless_range_loop,
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clippy::non_ascii_literal,
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clippy::redundant_clone,
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clippy::shadow_reuse,
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clippy::shadow_same,
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clippy::shadow_unrelated,
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clippy::single_match_else,
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clippy::str_to_string,
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clippy::string_slice,
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clippy::tests_outside_test_module,
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clippy::too_many_lines,
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clippy::unnecessary_wraps,
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clippy::unseparated_literal_suffix,
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clippy::use_debug,
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clippy::useless_vec,
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clippy::wildcard_enum_match_arm,
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clippy::else_if_without_else,
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clippy::expect_used,
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clippy::missing_const_for_fn,
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clippy::similar_names,
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clippy::type_complexity,
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clippy::collapsible_else_if,
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clippy::doc_lazy_continuation,
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clippy::items_after_test_module,
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clippy::map_clone,
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clippy::multiple_unsafe_ops_per_block,
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clippy::unwrap_or_default,
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clippy::assign_op_pattern,
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clippy::needless_borrow,
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clippy::println_empty_string,
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clippy::unnecessary_cast,
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clippy::used_underscore_binding,
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clippy::create_dir,
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clippy::implicit_saturating_sub,
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clippy::exit,
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clippy::expect_fun_call,
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clippy::too_many_arguments,
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clippy::unnecessary_map_or,
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clippy::unwrap_used,
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dead_code,
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unused_imports,
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unused_variables,
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clippy::cloned_ref_to_slice_refs,
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clippy::neg_multiply,
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clippy::while_let_loop,
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clippy::bool_assert_comparison,
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clippy::excessive_precision,
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clippy::trivially_copy_pass_by_ref,
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clippy::op_ref,
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clippy::redundant_closure,
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clippy::unnecessary_lazy_evaluations,
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clippy::if_then_some_else_none,
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clippy::unnecessary_to_owned,
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clippy::single_component_path_imports,
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)]
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//! Tests for PPO Hidden State Management
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//!
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//! Validates LSTM hidden state initialization, propagation, and reset logic.
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//! All state storage is host-side Vec<f32> (no Candle tensors).
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// candle eliminated -- HiddenStateManager uses host-side Vec<f32>
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use ml::ppo::hidden_state_manager::HiddenStateManager;
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#[test]
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fn test_hidden_state_initialization() -> Result<(), Box<dyn std::error::Error>> {
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// Test that hidden states are initialized to zeros
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let num_layers = 2;
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let batch_size = 4;
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let hidden_dim = 128;
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let manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?;
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let (policy_h, policy_c) = manager.get_policy_state();
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let (value_h, value_c) = manager.get_value_state();
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// Verify lengths (flat: num_layers * batch_size * hidden_dim)
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let expected_len = num_layers * batch_size * hidden_dim;
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assert_eq!(policy_h.len(), expected_len);
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assert_eq!(policy_c.len(), expected_len);
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assert_eq!(value_h.len(), expected_len);
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assert_eq!(value_c.len(), expected_len);
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// Verify all zeros
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let policy_h_sum: f32 = policy_h.iter().sum();
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let policy_c_sum: f32 = policy_c.iter().sum();
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let value_h_sum: f32 = value_h.iter().sum();
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let value_c_sum: f32 = value_c.iter().sum();
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assert_eq!(policy_h_sum, 0.0, "Policy hidden state should be zeros");
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assert_eq!(policy_c_sum, 0.0, "Policy cell state should be zeros");
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assert_eq!(value_h_sum, 0.0, "Value hidden state should be zeros");
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assert_eq!(value_c_sum, 0.0, "Value cell state should be zeros");
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Ok(())
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}
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#[test]
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fn test_hidden_state_propagation() -> Result<(), Box<dyn std::error::Error>> {
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// Test that hidden states carry across timesteps
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let num_layers = 2;
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let batch_size = 4;
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let hidden_dim = 128;
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let mut manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?;
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let total = num_layers * batch_size * hidden_dim;
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// Create new states with non-zero values
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let new_h = vec![1.0_f32; total];
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let new_c = vec![2.0_f32; total]; // c = 2.0 (was affine(2.0, 0.0) on ones)
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// Update policy states
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manager.update_policy_state(new_h.clone(), new_c.clone())?;
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// Verify states were updated
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let (policy_h, policy_c) = manager.get_policy_state();
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let policy_h_sum: f32 = policy_h.iter().sum();
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let policy_c_sum: f32 = policy_c.iter().sum();
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let expected_h_sum = total as f32;
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let expected_c_sum = total as f32 * 2.0;
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assert!(
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(policy_h_sum - expected_h_sum).abs() < 0.01,
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"Policy hidden state should be updated. Expected {}, got {}",
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expected_h_sum,
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policy_h_sum
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);
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assert!(
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(policy_c_sum - expected_c_sum).abs() < 0.01,
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"Policy cell state should be updated. Expected {}, got {}",
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expected_c_sum,
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policy_c_sum
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);
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// Update value states
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manager.update_value_state(new_h, new_c)?;
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// Verify value states were updated
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let (value_h, value_c) = manager.get_value_state();
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let value_h_sum: f32 = value_h.iter().sum();
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let value_c_sum: f32 = value_c.iter().sum();
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assert!(
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(value_h_sum - expected_h_sum).abs() < 0.01,
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"Value hidden state should be updated. Expected {}, got {}",
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expected_h_sum,
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value_h_sum
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);
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assert!(
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(value_c_sum - expected_c_sum).abs() < 0.01,
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"Value cell state should be updated. Expected {}, got {}",
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expected_c_sum,
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value_c_sum
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);
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Ok(())
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}
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#[test]
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fn test_hidden_state_reset_on_done() -> Result<(), Box<dyn std::error::Error>> {
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// Test that states reset when episodes end
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let num_layers = 2;
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let batch_size = 4;
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let hidden_dim = 128;
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let mut manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?;
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let total = num_layers * batch_size * hidden_dim;
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// Set states to non-zero (all ones)
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let ones = vec![1.0_f32; total];
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manager.update_policy_state(ones.clone(), ones.clone())?;
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manager.update_value_state(ones.clone(), ones.clone())?;
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// Create done mask: environments 0 and 2 are done (bool, not u8 tensor)
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let done_mask = vec![true, false, true, false];
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// Reset states for done environments
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manager.reset_on_done(&done_mask)?;
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// Verify policy states
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let (policy_h, policy_c) = manager.get_policy_state();
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// Check that environments 0 and 2 are reset (all zeros)
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// and environments 1 and 3 retain their values (all ones)
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for layer in 0..num_layers {
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for env in 0..batch_size {
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for dim in 0..hidden_dim {
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let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim;
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let expected = if env == 0 || env == 2 { 0.0 } else { 1.0 };
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assert!(
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(policy_h[idx] - expected).abs() < 0.01,
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"Policy hidden state at [{}, {}, {}] should be {}. Got {}",
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layer,
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env,
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dim,
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expected,
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policy_h[idx]
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);
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assert!(
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(policy_c[idx] - expected).abs() < 0.01,
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"Policy cell state at [{}, {}, {}] should be {}. Got {}",
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layer,
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env,
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dim,
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expected,
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policy_c[idx]
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);
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}
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}
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}
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// Verify value states similarly
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let (value_h, value_c) = manager.get_value_state();
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for layer in 0..num_layers {
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for env in 0..batch_size {
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for dim in 0..hidden_dim {
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let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim;
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let expected = if env == 0 || env == 2 { 0.0 } else { 1.0 };
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assert!(
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(value_h[idx] - expected).abs() < 0.01,
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"Value hidden state at [{}, {}, {}] should be {}. Got {}",
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layer,
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env,
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dim,
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expected,
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value_h[idx]
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);
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assert!(
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(value_c[idx] - expected).abs() < 0.01,
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"Value cell state at [{}, {}, {}] should be {}. Got {}",
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layer,
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env,
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dim,
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expected,
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value_c[idx]
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);
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}
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}
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}
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Ok(())
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}
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#[test]
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fn test_hidden_state_batching() -> Result<(), Box<dyn std::error::Error>> {
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// Test that manager handles multiple parallel environments correctly
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let num_layers = 2;
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let batch_size = 8; // 8 parallel environments
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let hidden_dim = 64;
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let mut manager = HiddenStateManager::with_defaults(num_layers, batch_size, hidden_dim)?;
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// Create different values for different environments
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let total = num_layers * batch_size * hidden_dim;
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let mut h_data = vec![0.0_f32; total];
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let mut c_data = vec![0.0_f32; total];
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for layer in 0..num_layers {
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for env in 0..batch_size {
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for dim in 0..hidden_dim {
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let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim;
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h_data[idx] = (env + 1) as f32; // Environment 0 = 1.0, env 1 = 2.0, etc.
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c_data[idx] = (env + 1) as f32 * 10.0; // Environment 0 = 10.0, env 1 = 20.0, etc.
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}
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}
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}
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// Update states (Vec<f32> directly, no Tensor conversion needed)
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manager.update_policy_state(h_data.clone(), c_data.clone())?;
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// Verify each environment has correct values
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let (policy_h, policy_c) = manager.get_policy_state();
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for layer in 0..num_layers {
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for env in 0..batch_size {
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for dim in 0..hidden_dim {
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let idx = layer * batch_size * hidden_dim + env * hidden_dim + dim;
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let expected_h = (env + 1) as f32;
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let expected_c = (env + 1) as f32 * 10.0;
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assert!(
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(policy_h[idx] - expected_h).abs() < 0.01,
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"Hidden state for env {} should be {}. Got {}",
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env,
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expected_h,
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policy_h[idx]
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);
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assert!(
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(policy_c[idx] - expected_c).abs() < 0.01,
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"Cell state for env {} should be {}. Got {}",
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env,
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expected_c,
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policy_c[idx]
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);
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}
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}
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}
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Ok(())
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}
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