Expand description
Core types and traits for the ToRSh deep learning framework
This crate provides fundamental building blocks used throughout ToRSh,
including error types, device abstractions, and core traits.
Re-exports§
pub use backend_detection::BackendFeatureDetector;pub use backend_detection::BackendSummary;pub use backend_detection::DeviceInfo;pub use backend_detection::PerformanceTier;pub use backend_detection::RuntimeFeatures;pub use backend_detection::WorkloadType;pub use device::Device;pub use device::DeviceCapabilities;pub use device::DeviceType;pub use dtype::AutoPromote;pub use dtype::Complex32;pub use dtype::Complex64;pub use dtype::ComplexElement;pub use dtype::DType;pub use dtype::FloatElement;pub use dtype::QInt8;pub use dtype::QUInt8;pub use dtype::TensorElement;pub use dtype::TypePromotion;pub use error::ErrorLocation;pub use error::Result;pub use error::TorshError;pub use ffi::TorshDType;pub use ffi::TorshDevice;pub use ffi::TorshErrorCode;pub use ffi::TorshShape;pub use interop::ArrowDataType;pub use interop::ArrowTypeInfo;pub use interop::ConversionUtils;pub use interop::FromExternal;pub use interop::FromExternalZeroCopy;pub use interop::InteropDocs;pub use interop::NumpyArrayInfo;pub use interop::OnnxDataType;pub use interop::OnnxTensorInfo;pub use interop::ToExternal;pub use interop::ToExternalZeroCopy;pub use memory_debug::detect_memory_leaks;pub use memory_debug::generate_memory_report;pub use memory_debug::get_memory_stats;pub use memory_debug::init_memory_debugger;pub use memory_debug::init_memory_debugger_with_config;pub use memory_debug::record_allocation;pub use memory_debug::record_deallocation;pub use memory_debug::AllocationInfo;pub use memory_debug::AllocationPattern;pub use memory_debug::DebuggingAllocator;pub use memory_debug::MemoryDebugConfig;pub use memory_debug::MemoryDebugger;pub use memory_debug::MemoryLeak;pub use memory_debug::MemoryReport;pub use memory_debug::MemoryStats;pub use memory_debug::SystemDebuggingAllocator;pub use memory_monitor::AllocationStrategy;pub use memory_monitor::MemoryMonitorConfig;pub use memory_monitor::MemoryPressure;pub use memory_monitor::MemoryPressureThresholds;pub use memory_monitor::SystemMemoryMonitor;pub use memory_monitor::SystemMemoryStats;pub use profiling::get_profiler;pub use profiling::init_profiler;pub use profiling::profile_closure;pub use profiling::OperationContext;pub use profiling::OperationHandle;pub use profiling::OperationRecord;pub use profiling::OperationStats;pub use profiling::OperationType;pub use profiling::PerformanceBottleneck;pub use profiling::PerformanceProfiler;pub use profiling::ProfilerConfig;pub use shape::Shape;pub use simd_arm::ArmSimdOps;pub use sparse::CompressionStats;pub use sparse::CooIndices;pub use sparse::CooStorage;pub use sparse::CsrIndices;pub use sparse::CsrStorage;pub use sparse::SparseFormat;pub use sparse::SparseMetadata;pub use sparse::SparseStorage;pub use storage::allocate_pooled;pub use storage::clear_pooled_memory;pub use storage::deallocate_pooled;pub use storage::pooled_memory_stats;pub use storage::MemoryFormat;pub use storage::MemoryPool;pub use storage::PoolStats;pub use storage::Storage;pub use storage::StorageView;pub use scirs2;
Modules§
- backend_
detection - Backend feature detection system for runtime capability discovery
- device
- Device abstraction and management system
- dtype
- error
- Error types for ToRSh - Clean Modular Interface
- error_
recovery - Error recovery mechanisms for graceful degradation
- examples
- Comprehensive examples for torsh-core modules
- ffi
- FFI-safe type wrappers for C/C++ integration
- inspector
- Tensor Inspector
- interop
- Interoperability traits and utilities for ToRSh
- memory_
debug - Memory debugging and allocation tracking tools for ToRSh
- memory_
monitor - Advanced system memory monitoring with platform-specific APIs
- prelude
- Prelude module for convenient imports
- profiling
- Performance Profiling Hooks for ToRSh Operations
- shape
- Shape and stride utilities for tensors
- shape_
debug - Shape Debugging Utilities
- simd_
arm - ARM NEON SIMD optimizations for ToRSh core operations
- sparse
- storage
- Storage system for tensor data management
Macros§
- impl_
custom_ tensor_ element - Helper macro for easily implementing CustomTensorElement for simple types
- index_
error - Convenience macro for index errors
- profile_
operation - Convenience macro for profiling operations
- profile_
shape_ op - Macro for easy shape operation profiling
- shape_
mismatch_ error - Convenience macro for shape mismatch errors
- torsh_
error_ with_ location - Convenience macros for error creation with location information