realizar 0.8.6

#[cfg(test)]
#[cfg(feature = "cuda")]
mod tests {
    use super::*;
    use crate::cuda::executor::test_fixtures::generate_q4_0_weights;

    /// Helper to create CudaExecutor for tests
    fn create_executor() -> Option<CudaExecutor> {
        CudaExecutor::new(0).ok()
    }

    /// Helper to setup FFN weights in executor cache
    fn setup_ffn_weights(
        exec: &mut CudaExecutor,
        hidden_dim: u32,
        intermediate_dim: u32,
    ) -> Result<(), GpuError> {
        // Q4_K: 144 bytes per 256 elements
        // Gate: [intermediate_dim, hidden_dim]
        let gate_blocks = (intermediate_dim as usize) * (hidden_dim as usize / 256);
        let gate_weights = vec![0u8; gate_blocks * 144];
        exec.load_quantized_weights("ffn_gate", &gate_weights)?;

        // Up: [intermediate_dim, hidden_dim]
        let up_weights = vec![0u8; gate_blocks * 144];
        exec.load_quantized_weights("ffn_up", &up_weights)?;

        // Down: [hidden_dim, intermediate_dim]
        let down_blocks = (hidden_dim as usize) * (intermediate_dim as usize / 256);
        let down_weights = vec![0u8; down_blocks * 144];
        exec.load_quantized_weights("ffn_down", &down_weights)?;

        Ok(())
    }

    #[test]
    fn test_fused_ffn_swiglu_gpu_path_selection() {
        let Some(mut exec) = create_executor() else {
            return;
        };

        // Test path: hidden_dim % 256 != 0 should use q4k_gemv_cached_async
        let hidden_dim = 512u32; // 512 % 256 == 0, aligned
        let intermediate_dim = 1024u32;

        // Setup weights
        if setup_ffn_weights(&mut exec, hidden_dim, intermediate_dim).is_err() {
            return;
        }

        // Create input
        let input: Vec<f32> = (0..hidden_dim as usize)
            .map(|i| (i as f32) * 0.001)
            .collect();
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        // Execute FFN (may fail due to kernel issues, but exercises path selection)
        let result = fused_ffn_swiglu_gpu(
            &mut exec,
            &input_buf,
            "ffn_gate",
            "ffn_up",
            "ffn_down",
            hidden_dim,
            intermediate_dim,
        );
        // Result may fail due to kernel compilation, but path selection is exercised
        let _ = result;
    }

    #[test]
    fn test_fused_ffn_swiglu_gpu_unaligned() {
        let Some(mut exec) = create_executor() else {
            return;
        };

        // Test path: hidden_dim % 256 != 0 (unaligned)
        // This should use the fallback q4k_gemv_cached_async path
        let hidden_dim = 256u32; // Minimum aligned size
        let intermediate_dim = 768u32; // 768 % 256 == 0

        // For Q4_0 format (18 bytes/32 elements) instead of Q4_K
        let gate_blocks = (intermediate_dim as usize) * (hidden_dim as usize / 32);
        let gate_weights = generate_q4_0_weights(gate_blocks);
        let _ = exec.load_quantized_weights("ffn_gate_unaligned", &gate_weights);

        let up_weights = generate_q4_0_weights(gate_blocks);
        let _ = exec.load_quantized_weights("ffn_up_unaligned", &up_weights);

        let down_blocks = (hidden_dim as usize) * (intermediate_dim as usize / 32);
        let down_weights = generate_q4_0_weights(down_blocks);
        let _ = exec.load_quantized_weights("ffn_down_unaligned", &down_weights);

        let input: Vec<f32> = vec![0.1f32; hidden_dim as usize];
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        // This tests the unaligned path (even though setup may not be perfect for Q4K)
        let result = fused_ffn_swiglu_gpu(
            &mut exec,
            &input_buf,
            "ffn_gate_unaligned",
            "ffn_up_unaligned",
            "ffn_down_unaligned",
            hidden_dim,
            intermediate_dim,
        );
        let _ = result;
    }

    #[test]
    fn test_fused_ffn_chunk_threshold() {
        let Some(mut exec) = create_executor() else {
            return;
        };

        // Test CHUNK_THRESHOLD behavior
        // hidden_dim > 8192 should use non-dp4a path
        let hidden_dim = 256u32; // Within threshold
        let intermediate_dim = 512u32;

        if setup_ffn_weights(&mut exec, hidden_dim, intermediate_dim).is_err() {
            return;
        }

        let input: Vec<f32> = vec![0.1f32; hidden_dim as usize];
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        let result = fused_ffn_swiglu_gpu(
            &mut exec,
            &input_buf,
            "ffn_gate",
            "ffn_up",
            "ffn_down",
            hidden_dim,
            intermediate_dim,
        );
        let _ = result;
    }

    #[test]
    fn test_fused_ffn_swiglu_gpu_true_dp4a() {
        let Some(mut exec) = create_executor() else {
            return;
        };

        // Test the TRUE_DP4A path directly
        let hidden_dim = 256u32;
        let intermediate_dim = 512u32;

        if setup_ffn_weights(&mut exec, hidden_dim, intermediate_dim).is_err() {
            return;
        }

        let input: Vec<f32> = (0..hidden_dim as usize)
            .map(|i| (i as f32) * 0.001)
            .collect();
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        // Call the true_dp4a variant directly
        let result = fused_ffn_swiglu_gpu_true_dp4a(
            &mut exec,
            &input_buf,
            "ffn_gate",
            "ffn_up",
            "ffn_down",
            hidden_dim,
            intermediate_dim,
        );
        // May fail due to kernel issues, but exercises the path
        let _ = result;
    }

    // ========================================================================
    // Coverage Tests: FFN with ModelHarness (v1.36.0)
    // ========================================================================

    #[test]
    fn test_ffn_with_harness() {
        use crate::cuda::executor::test_fixtures::{setup_executor_harness, HarnessConfig};
        let Some(mut exec) = create_executor() else {
            return;
        };
        let config = HarnessConfig::default();
        if setup_executor_harness(&mut exec, &config).is_err() {
            return;
        }

        let input: Vec<f32> = vec![0.1f32; config.hidden_dim];
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        let result = fused_ffn_swiglu_gpu(
            &mut exec,
            &input_buf,
            "blk.0.ffn_gate",
            "blk.0.ffn_up",
            "blk.0.ffn_down",
            config.hidden_dim as u32,
            config.intermediate_dim as u32,
        );
        let _ = result;
    }

    #[test]
    fn test_ffn_different_layers() {
        use crate::cuda::executor::test_fixtures::{setup_executor_harness, HarnessConfig};
        let Some(mut exec) = create_executor() else {
            return;
        };
        let mut config = HarnessConfig::default();
        config.num_layers = 4;
        if setup_executor_harness(&mut exec, &config).is_err() {
            return;
        }

        for layer_idx in 0..config.num_layers {
            let input: Vec<f32> = vec![0.1f32; config.hidden_dim];
            let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

            let result = fused_ffn_swiglu_gpu(
                &mut exec,
                &input_buf,
                &format!("blk.{}.ffn_gate", layer_idx),
                &format!("blk.{}.ffn_up", layer_idx),
                &format!("blk.{}.ffn_down", layer_idx),
                config.hidden_dim as u32,
                config.intermediate_dim as u32,
            );
            let _ = result;
        }
    }

    #[test]
    fn test_ffn_varying_inputs() {
        use crate::cuda::executor::test_fixtures::{setup_executor_harness, HarnessConfig};
        let Some(mut exec) = create_executor() else {
            return;
        };
        let config = HarnessConfig::default();
        if setup_executor_harness(&mut exec, &config).is_err() {
            return;
        }

        // Test with different input patterns
        let inputs = [
            vec![0.0f32; config.hidden_dim],
            vec![1.0f32; config.hidden_dim],
            (0..config.hidden_dim)
                .map(|i| (i as f32 / 1000.0).sin())
                .collect::<Vec<_>>(),
        ];

        for input in inputs {
            let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

            let result = fused_ffn_swiglu_gpu(
                &mut exec,
                &input_buf,
                "blk.0.ffn_gate",
                "blk.0.ffn_up",
                "blk.0.ffn_down",
                config.hidden_dim as u32,
                config.intermediate_dim as u32,
            );
            let _ = result;
        }
    }

    #[test]
    fn test_ffn_true_dp4a_with_harness() {
        use crate::cuda::executor::test_fixtures::{setup_executor_harness, HarnessConfig};
        let Some(mut exec) = create_executor() else {
            return;
        };
        let config = HarnessConfig::default();
        if setup_executor_harness(&mut exec, &config).is_err() {
            return;
        }

        let input: Vec<f32> = (0..config.hidden_dim).map(|i| (i as f32) * 0.001).collect();
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        // Call true_dp4a variant with harness weights
        let result = fused_ffn_swiglu_gpu_true_dp4a(
            &mut exec,
            &input_buf,
            "blk.0.ffn_gate",
            "blk.0.ffn_up",
            "blk.0.ffn_down",
            config.hidden_dim as u32,
            config.intermediate_dim as u32,
        );
        let _ = result;
    }

    #[test]
    fn test_ffn_larger_intermediate_dim() {
        use crate::cuda::executor::test_fixtures::{setup_executor_harness, HarnessConfig};
        let Some(mut exec) = create_executor() else {
            return;
        };
        let mut config = HarnessConfig::default();
        config.intermediate_dim = 2048; // Larger intermediate
        if setup_executor_harness(&mut exec, &config).is_err() {
            return;
        }

        let input: Vec<f32> = vec![0.1f32; config.hidden_dim];
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        let result = fused_ffn_swiglu_gpu(
            &mut exec,
            &input_buf,
            "blk.0.ffn_gate",
            "blk.0.ffn_up",
            "blk.0.ffn_down",
            config.hidden_dim as u32,
            config.intermediate_dim as u32,
        );
        let _ = result;
    }

    #[test]
    fn test_ffn_output_dimensions() {
        use crate::cuda::executor::test_fixtures::{setup_executor_harness, HarnessConfig};
        let Some(mut exec) = create_executor() else {
            return;
        };
        let config = HarnessConfig::default();
        if setup_executor_harness(&mut exec, &config).is_err() {
            return;
        }

        let input: Vec<f32> = vec![0.1f32; config.hidden_dim];
        let input_buf = GpuBuffer::from_host(&exec.context, &input).expect("input_buf");

        let result = fused_ffn_swiglu_gpu(
            &mut exec,
            &input_buf,
            "blk.0.ffn_gate",
            "blk.0.ffn_up",
            "blk.0.ffn_down",
            config.hidden_dim as u32,
            config.intermediate_dim as u32,
        );

        // If successful, output should have hidden_dim elements
        if let Ok(output_buf) = result {
            let mut output = vec![0.0f32; config.hidden_dim];
            output_buf.copy_to_host(&mut output).expect("copy");
            assert_eq!(
                output.len(),
                config.hidden_dim,
                "FFN output should match hidden_dim"
            );
        }
    }
}