// Copyright 2025 Neuraville Inc.
// SPDX-License-Identifier: Apache-2.0

/// Hailo-8 Neural Accelerator Platform
///
/// Hailo-8 is a neural network accelerator delivering 26 TOPS (Tera Operations Per Second)
/// with ultra-low power consumption (2.5W typical).
///
/// **Capabilities**:
/// - 26 TOPS performance
/// - Native INT8 quantization support
/// - 1,000,000+ neuron capacity
/// - PCIe, Ethernet, USB interfaces
/// - Power: 2.5W typical, 5W max
///
/// **Perfect for**:
/// - Large-scale spiking neural networks (1M+ neurons)
/// - Real-time inference at high frequency
/// - Edge AI applications
/// - Robotics with vision processing
///
/// **Integration**:
/// Hailo-8 uses HailoRT (C/C++ API). This implementation provides the architecture
/// for integration. Full implementation requires FFI bindings to HailoRT.
use crate::hal::*;

/// Hailo-8 accelerator platform
#[cfg(feature = "hailo")]
pub struct Hailo8Accelerator {
    device_id: u32,
    is_initialized: bool,
    max_neurons: usize,
    max_synapses: usize,
}

#[cfg(feature = "hailo")]
impl Hailo8Accelerator {
    /// Initialize Hailo-8 accelerator
    ///
    /// # Returns
    /// Initialized Hailo8Accelerator or error
    ///
    /// # Example
    /// ```no_run
    /// let hailo = Hailo8Accelerator::init().expect("Failed to init Hailo-8");
    /// ```
    pub fn init() -> Result<Self, HailoError> {
        // In real implementation, this would:
        // 1. Call hailo_init() from HailoRT
        // 2. Scan for available devices
        // 3. Open first available device
        // 4. Query device capabilities
        // 5. Allocate device memory for neurons/synapses

        // For now, return a mock initialized state
        Ok(Self {
            device_id: 0,
            is_initialized: true,
            max_neurons: 1_000_000,   // Hailo-8 can handle 1M+ neurons
            max_synapses: 10_000_000, // 10M+ synapses
        })
    }

    /// Get device capabilities
    pub fn capabilities(&self) -> AcceleratorCapabilities {
        AcceleratorCapabilities {
            max_neurons: self.max_neurons,
            max_synapses: self.max_synapses,
            supported_precisions: 0b001, // INT8 supported (bit 0)
            memory_bandwidth_bytes_per_sec: 1_000_000_000, // 1 GB/s estimate
            power_consumption_mw: 2500,  // 2.5W typical
        }
    }

    /// Get device temperature (for monitoring)
    pub fn temperature_celsius(&self) -> Result<f32, HailoError> {
        // Would query device thermal sensors
        Ok(45.0) // Placeholder
    }

    /// Get device utilization (0.0 to 1.0)
    pub fn utilization(&self) -> Result<f32, HailoError> {
        // Would query device performance counters
        Ok(0.5) // Placeholder
    }
}

#[cfg(feature = "hailo")]
impl NeuralAccelerator for Hailo8Accelerator {
    type Error = HailoError;

    fn is_available(&self) -> bool {
        self.is_initialized
    }

    fn name(&self) -> &'static str {
        "Hailo-8"
    }

    fn performance_ops_per_sec(&self) -> u64 {
        26_000_000_000_000 // 26 TOPS = 26 trillion operations per second
    }

    fn upload_neurons(&mut self, neurons: &[u8]) -> Result<(), Self::Error> {
        if !self.is_initialized {
            return Err(HailoError::NotInitialized);
        }

        // In real implementation, this would:
        // 1. Validate neuron data format (INT8Value serialization)
        // 2. Allocate device memory if needed
        // 3. DMA transfer to Hailo device memory
        // 4. Call hailo_upload_input_buffer()

        // For now, validate size
        let expected_size = self.max_neurons * 15; // 15 bytes per neuron (INT8)
        if neurons.len() > expected_size {
            return Err(HailoError::BufferTooLarge);
        }

        Ok(())
    }

    fn upload_synapses(&mut self, synapses: &[u8]) -> Result<(), Self::Error> {
        if !self.is_initialized {
            return Err(HailoError::NotInitialized);
        }

        // In real implementation, this would:
        // 1. Convert synapse data to Hailo format
        // 2. Upload to device memory
        // 3. Configure connectivity matrix

        let expected_size = self.max_synapses * 7; // 7 bytes per synapse
        if synapses.len() > expected_size {
            return Err(HailoError::BufferTooLarge);
        }

        Ok(())
    }

    fn process_burst(&mut self) -> Result<u32, Self::Error> {
        if !self.is_initialized {
            return Err(HailoError::NotInitialized);
        }

        // In real implementation, this would:
        // 1. Call hailo_run_inference()
        // 2. Wait for completion (async or blocking)
        // 3. Read firing count from output buffer
        // 4. Return number of neurons that fired

        // For now, return placeholder
        Ok(0)
    }

    fn download_neurons(&mut self, _buffer: &mut [u8]) -> Result<usize, Self::Error> {
        if !self.is_initialized {
            return Err(HailoError::NotInitialized);
        }

        // In real implementation, this would:
        // 1. Call hailo_read_output_buffer()
        // 2. DMA transfer from device memory
        // 3. Deserialize updated neuron states
        // 4. Copy to provided buffer

        Ok(0) // Placeholder
    }

    fn reset(&mut self) -> Result<(), Self::Error> {
        if !self.is_initialized {
            return Err(HailoError::NotInitialized);
        }

        // In real implementation, this would:
        // 1. Reset device state
        // 2. Clear all buffers
        // 3. Reset performance counters

        Ok(())
    }
}

/// Hailo-8 error types
#[derive(Debug, Clone, Copy, PartialEq, Eq)]
pub enum HailoError {
    /// Device not initialized
    NotInitialized,
    /// No Hailo device found
    NoDeviceFound,
    /// Device busy
    DeviceBusy,
    /// Buffer too large for device
    BufferTooLarge,
    /// DMA transfer failed
    DmaError,
    /// Inference failed
    InferenceFailed,
    /// Timeout waiting for device
    Timeout,
    /// Invalid parameter
    InvalidParameter,
    /// Device error
    DeviceError,
}

// Placeholder for when hailo feature is not enabled
#[cfg(not(feature = "hailo"))]
pub struct Hailo8Accelerator;

#[cfg(not(feature = "hailo"))]
impl Hailo8Accelerator {
    pub fn init() -> Result<Self, &'static str> {
        Err("Hailo feature not enabled. Rebuild with --features hailo")
    }
}

// FFI bindings to HailoRT (placeholder for actual implementation)
#[cfg(feature = "hailo")]
mod ffi {
    // In real implementation, this would be:
    // extern "C" {
    //     fn hailo_init() -> i32;
    //     fn hailo_scan_devices(devices: *mut u32, count: *mut u32) -> i32;
    //     fn hailo_create_vdevice(params: *const HailoVDeviceParams, device: *mut HailoDevice) -> i32;
    //     fn hailo_upload_input_buffer(device: HailoDevice, name: *const i8, data: *const u8, size: usize) -> i32;
    //     fn hailo_run_inference(device: HailoDevice, timeout: u32) -> i32;
    //     fn hailo_read_output_buffer(device: HailoDevice, name: *const i8, buffer: *mut u8, size: usize) -> i32;
    //     fn hailo_release_device(device: HailoDevice) -> i32;
    // }

    // Placeholder types for architecture demonstration
    #[allow(dead_code)]
    pub type HailoDevice = usize;

    #[allow(dead_code)]
    pub struct HailoVDeviceParams {
        pub device_count: u32,
        pub scheduling_algorithm: u32,
    }
}

/// Hybrid execution mode: CPU + Hailo accelerator
///
/// This allows running small networks on CPU (low latency) and large networks
/// on Hailo (high throughput).
#[cfg(feature = "hailo")]
pub struct HybridCpuHailo<const CPU_NEURONS: usize, const CPU_SYNAPSES: usize> {
    /// CPU-side neurons (for low-latency processing)
    cpu_neurons: crate::NeuronArray<crate::INT8Value, CPU_NEURONS>,

    /// CPU-side synapses
    cpu_synapses: crate::SynapseArray<CPU_SYNAPSES>,

    /// Hailo accelerator
    hailo: Hailo8Accelerator,
}

#[cfg(feature = "hailo")]
impl<const CPU_NEURONS: usize, const CPU_SYNAPSES: usize>
    HybridCpuHailo<CPU_NEURONS, CPU_SYNAPSES>
{
    /// Create hybrid CPU+Hailo execution engine
    pub fn new() -> Result<Self, HailoError> {
        Ok(Self {
            cpu_neurons: crate::NeuronArray::new(),
            cpu_synapses: crate::SynapseArray::new(),
            hailo: Hailo8Accelerator::init()?,
        })
    }

    /// Process burst using both CPU and Hailo
    ///
    /// Strategy:
    /// - Process CPU neurons locally (low latency, small networks)
    /// - Offload large networks to Hailo (high throughput)
    ///
    /// # Arguments
    /// * `cpu_inputs` - Input currents for CPU neurons (fixed-size array)
    /// * `cpu_fired` - Output mask for CPU neurons that fired
    ///
    /// # Returns
    /// Total number of neurons that fired (CPU + Hailo)
    pub fn process_burst_hybrid(
        &mut self,
        cpu_inputs: &[crate::INT8Value; CPU_NEURONS],
        cpu_fired: &mut [bool; CPU_NEURONS],
    ) -> Result<u32, HailoError> {
        // Step 1: Process CPU neurons (low latency)
        let cpu_fired_count = self.cpu_neurons.process_burst(cpu_inputs, cpu_fired) as u32;

        // Step 2: Process Hailo neurons (high throughput)
        let hailo_fired_count = self.hailo.process_burst()?;

        // Step 3: Combine results
        Ok(cpu_fired_count + hailo_fired_count)
    }

    /// Get accelerator reference
    pub fn accelerator(&mut self) -> &mut Hailo8Accelerator {
        &mut self.hailo
    }
}
