optirs-tpu 0.3.1

use std::fmt::Debug;
// Core XLA Types and Data Structures
//
// This module defines the fundamental types used throughout the XLA compilation system,
// including operations, operands, shapes, layouts, and performance characteristics.

use scirs2_core::ndarray::Array1;
use scirs2_core::numeric::Float;
use std::collections::HashMap;
use std::time::Instant;

/// Unique computation identifier
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub struct ComputationId(pub u64);

/// Unique operation identifier
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub struct OperationId(pub usize);

/// XLA operation representation
#[derive(Debug, Clone)]
pub struct XLAOperation<T: Float + Debug + Send + Sync + 'static> {
    /// Operation ID
    pub id: OperationId,

    /// Operation type
    pub op_type: OperationType,

    /// Input operands
    pub inputs: Vec<Operand<T>>,

    /// Output specifications
    pub outputs: Vec<OperandType<T>>,

    /// Operation attributes
    pub attributes: OperationAttributes,

    /// Source location (for debugging)
    pub source_location: Option<SourceLocation>,

    /// Performance characteristics
    pub performance_characteristics: OperationPerformanceCharacteristics,

    /// Memory requirements
    pub memory_requirements: OperationMemoryRequirements,
}

/// Types of XLA operations
#[derive(Debug, Clone, PartialEq)]
pub enum OperationType {
    // Arithmetic operations
    Add,
    Subtract,
    Multiply,
    Divide,
    Power,
    Sqrt,
    Exp,
    Log,
    Sin,
    Cos,
    Tanh,

    // Linear algebra operations
    Dot,
    MatMul,
    Transpose,

    // Reduction operations
    Reduce(ReduceOperation),
    AllReduce(AllReduceOperation),

    // Shape operations
    Reshape,
    Broadcast,
    Slice,
    Concatenate,

    // Activation functions
    ReLU,
    Sigmoid,
    GELU,
    Swish,

    // Normalization operations
    BatchNorm,
    LayerNorm,

    // Convolution operations
    Convolution(ConvolutionConfig),

    // Control flow operations
    Conditional,
    While,
    Call,

    // Communication operations
    AllGather,
    AllToAll,
    CollectivePermute,

    // Custom operations
    Custom(CustomOperation),

    // Optimizer-specific operations
    OptimizerUpdate(OptimizerUpdateType),
}

/// Reduce operation configuration
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub struct ReduceOperation {
    pub reduce_function: ReduceFunction,
    pub dimensions: Vec<usize>,
    pub keep_dims: bool,
}

/// Reduce function types
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum ReduceFunction {
    Sum,
    Product,
    Min,
    Max,
    Mean,
    And,
    Or,
}

/// All-reduce operation configuration
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub struct AllReduceOperation {
    pub reduce_function: ReduceFunction,
    pub replica_groups: Vec<Vec<usize>>,
    pub channel_id: Option<u64>,
}

/// Convolution operation configuration
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub struct ConvolutionConfig {
    pub strides: Vec<usize>,
    pub padding: PaddingConfig,
    pub dilation: Vec<usize>,
    pub feature_group_count: usize,
    pub batch_group_count: usize,
}

/// Padding configuration
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum PaddingConfig {
    Same,
    Valid,
    Explicit(Vec<(usize, usize)>),
}

/// Custom operation definition
#[derive(Debug, Clone, PartialEq)]
pub struct CustomOperation {
    pub name: String,
    pub version: u32,
    pub attributes: HashMap<String, AttributeValue>,
    pub has_side_effects: bool,
}

/// Optimizer update types
#[derive(Debug, Clone, PartialEq, Eq, Hash)]
pub enum OptimizerUpdateType {
    SGD,
    Adam,
    RMSprop,
    AdaGrad,
    Custom(String),
}

/// Operation operand
#[derive(Debug, Clone)]
pub struct Operand<T: Float + Debug + Send + Sync + 'static> {
    /// Operand ID
    pub id: OperandId,

    /// Operand type
    pub operand_type: OperandType<T>,

    /// Source operation (if computed)
    pub source_operation: Option<OperationId>,

    /// Operand metadata
    pub metadata: OperandMetadata,
}

/// Unique operand identifier
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub struct OperandId(pub usize);

/// Operand type specification
#[derive(Debug, Clone)]
pub enum OperandType<T: Float + Debug + Send + Sync + 'static> {
    /// Tensor with shape and element type
    Tensor {
        shape: TensorShape,
        element_type: ElementType,
        layout: Option<Layout>,
    },

    /// Scalar value
    Scalar { value: T, element_type: ElementType },

    /// Constant tensor
    Constant {
        values: Array1<T>,
        shape: TensorShape,
        element_type: ElementType,
    },

    /// Tuple of operands
    Tuple(Vec<OperandType<T>>),

    /// Token for ordering
    Token,
}

/// Tensor shape representation
#[derive(Debug, Clone, PartialEq, Eq)]
pub struct TensorShape {
    pub dimensions: Vec<usize>,
    pub is_dynamic: Vec<bool>,
}

/// XLA element types
#[derive(Debug, Clone, Copy, PartialEq, Eq, Hash)]
pub enum ElementType {
    F16,
    F32,
    F64,
    BF16,
    S8,
    S16,
    S32,
    S64,
    U8,
    U16,
    U32,
    U64,
    C64,
    C128,
    Bool,
    Token,
}

/// Memory layout specification
#[derive(Debug, Clone)]
pub struct Layout {
    pub minor_to_major: Vec<usize>,
    pub tiles: Vec<Tile>,
    pub element_size_in_bits: usize,
    pub memory_space: MemorySpace,
}

/// Layout tile
#[derive(Debug, Clone)]
pub struct Tile {
    pub dimensions: Vec<usize>,
}

/// Memory space specification
#[derive(Debug, Clone, Copy)]
pub enum MemorySpace {
    Default,
    Host,
    Device,
    Unified,
}

/// Operation attributes
#[derive(Debug, Clone)]
pub struct OperationAttributes {
    pub attributes: HashMap<String, AttributeValue>,
}

/// Attribute value types
#[derive(Debug, Clone, PartialEq)]
pub enum AttributeValue {
    Bool(bool),
    Int(i64),
    Float(f64),
    String(String),
    IntList(Vec<i64>),
    FloatList(Vec<f64>),
    StringList(Vec<String>),
}

/// Source location for debugging
#[derive(Debug, Clone)]
pub struct SourceLocation {
    pub file: String,
    pub line: u32,
    pub column: u32,
    pub function: String,
}

/// Operation performance characteristics
#[derive(Debug, Clone)]
pub struct OperationPerformanceCharacteristics {
    /// Estimated FLOPs
    pub flops: u64,

    /// Estimated execution time (microseconds)
    pub execution_time_us: u64,

    /// Memory bandwidth requirement (GB/s)
    pub memory_bandwidth: f64,

    /// Compute intensity (FLOPs/byte)
    pub compute_intensity: f64,

    /// Parallelization potential
    pub parallelization_potential: f64,

    /// TPU utilization estimate
    pub tpu_utilization: f64,
}

/// Operation memory requirements
#[derive(Debug, Clone)]
pub struct OperationMemoryRequirements {
    /// Input memory (bytes)
    pub input_memory: usize,

    /// Output memory (bytes)
    pub output_memory: usize,

    /// Temporary memory (bytes)
    pub temp_memory: usize,

    /// Peak memory usage (bytes)
    pub peak_memory: usize,

    /// Memory access pattern
    pub access_pattern: MemoryAccessPattern,
}

/// Memory access patterns
#[derive(Debug, Clone, Copy)]
pub enum MemoryAccessPattern {
    Sequential,
    Random,
    Strided,
    Broadcast,
    Gather,
    Scatter,
}

/// Input specification
#[derive(Debug, Clone)]
pub struct InputSpecification<T: Float + Debug + Send + Sync + 'static> {
    pub name: String,
    pub operand_type: OperandType<T>,
    pub is_parameter: bool,
}

/// Output specification
#[derive(Debug, Clone)]
pub struct OutputSpecification<T: Float + Debug + Send + Sync + 'static> {
    pub name: String,
    pub operand_type: OperandType<T>,
    pub operand_id: OperandId,
}

/// Computation metadata
#[derive(Debug, Clone)]
pub struct ComputationMetadata {
    pub creation_time: Instant,
    pub estimated_flops: u64,
    pub estimated_memory: usize,
    pub complexity_score: f64,
    pub optimization_opportunities: Vec<OptimizationOpportunity>,
}

/// XLA computation representation
#[derive(Debug, Clone)]
pub struct XLAComputation<T: Float + Debug + Send + Sync + 'static> {
    /// Computation identifier
    pub id: ComputationId,

    /// Operations in topological order
    pub operations: Vec<XLAOperation<T>>,

    /// Input specifications
    pub inputs: Vec<InputSpecification<T>>,

    /// Output specifications
    pub outputs: Vec<OutputSpecification<T>>,

    /// Computation metadata
    pub metadata: ComputationMetadata,

    /// Operand graph
    pub operands: HashMap<OperandId, Operand<T>>,

    /// Operation dependencies
    pub dependencies: HashMap<OperationId, Vec<OperationId>>,
}

/// Optimization opportunity
#[derive(Debug, Clone)]
pub struct OptimizationOpportunity {
    pub opportunity_type: OptimizationOpportunityType,
    pub estimated_benefit: f64,
    pub implementation_cost: f64,
    pub description: String,
}

/// Types of optimization opportunities
#[derive(Debug, Clone, Copy)]
pub enum OptimizationOpportunityType {
    OperatorFusion,
    LayoutOptimization,
    MemoryOptimization,
    ParallelizationOpportunity,
    ConstantFolding,
    DeadCodeElimination,
    CommonSubexpressionElimination,
    LoopOptimization,
}

/// Performance hint
#[derive(Debug, Clone)]
pub struct PerformanceHint {
    pub hint_type: PerformanceHintType,
    pub target_operations: Vec<OperationId>,
    pub parameters: HashMap<String, AttributeValue>,
}

/// Types of performance hints
#[derive(Debug, Clone, Copy)]
pub enum PerformanceHintType {
    PreferTensorCores,
    MinimizeMemoryBandwidth,
    MaximizeParallelism,
    OptimizeForLatency,
    OptimizeForThroughput,
    PreferLocalMemory,
    AvoidSynchronization,
}

/// Layout hint
#[derive(Debug, Clone)]
pub struct LayoutHint {
    pub target_operand: OperandId,
    pub preferred_layout: Layout,
    pub priority: LayoutPriority,
}

/// Layout priority levels
#[derive(Debug, Clone, Copy)]
pub enum LayoutPriority {
    Low,
    Medium,
    High,
    Critical,
}

/// Operand metadata
#[derive(Debug, Clone)]
pub struct OperandMetadata {
    pub name: Option<String>,
    pub description: Option<String>,
    pub source_info: Option<SourceLocation>,
    pub usage_hints: Vec<UsageHint>,
}

/// Usage hint for operands
#[derive(Debug, Clone)]
pub struct UsageHint {
    pub hint_type: UsageHintType,
    pub confidence: f64,
}

/// Types of usage hints
#[derive(Debug, Clone, Copy)]
pub enum UsageHintType {
    HighFrequencyAccess,
    SequentialAccess,
    RandomAccess,
    ReadOnly,
    WriteOnly,
    ReadWrite,
    Temporary,
    Persistent,
}