| Cmxnet::Imperative::AGInfo | |
| Cmxnet::engine::CallbackOnComplete | OnComplete Callback to the engine, called by AsyncFn when action completes |
| Cmxnet::Context | Context information about the execution environment |
| Cmxnet::cpp::Context | Context interface |
| Cmxnet::common::csr_idx_check | Indices should be non-negative, less than the number of columns and in ascending order per row |
| Cmxnet::common::csr_indptr_check | IndPtr should be non-negative, in non-decreasing order, start with 0 and end with value equal with size of indices |
| Cmxnet::DataBatch | DataBatch of NDArray, returned by Iterator |
| Cmxnet::cpp::DataBatch | Default object for holding a mini-batch of data and related information |
| Cmxnet::DataInst | Single data instance |
| ►CDataIter | |
| Cmxnet::IIterator< DType > | Iterator type |
| ►Cmxnet::cpp::DataIter | |
| Cmxnet::cpp::MXDataIter | |
| Cmxnet::common::cuda::DeviceStore | |
| Cmxnet::Engine | Dependency engine that schedules operations |
| Cmxnet::features::EnumNames | |
| Cmxnet::op::EnvArguments | Environment arguments that is used by the function. These can be things like scalar arguments when add a value with scalar |
| ►Cmxnet::cpp::EvalMetric | |
| Cmxnet::cpp::Accuracy | |
| Cmxnet::cpp::LogLoss | |
| Cmxnet::cpp::MAE | |
| Cmxnet::cpp::MSE | |
| Cmxnet::cpp::PSNR | |
| Cmxnet::cpp::RMSE | |
| Cmxnet::cpp::Executor | Executor interface |
| Cmxnet::Executor | Executor of a computation graph. Executor can be created by Binding a symbol |
| Cmxnet::cpp::FeedForward | |
| Cmxnet::cpp::FeedForwardConfig | |
| ►CFieldEntryBase | |
| Cdmlc::parameter::FieldEntry< mxnet::TShape > | |
| ►CFunctionRegEntryBase | |
| Cmxnet::DataIteratorReg | Registry entry for DataIterator factory functions |
| Cmxnet::NDArrayFunctionReg | Registry entry for NDArrayFunction |
| Cmxnet::OperatorPropertyReg | Registry entry for OperatorProperty factory functions |
| Cmxnet::GPUAuxStream | Holds an auxiliary mshadow gpu stream that can be synced with a primary stream |
| ►Cmxnet::op::GradFunctionArgument | Super class of all gradient function argument |
| Cmxnet::op::Input0 | First input to the function |
| Cmxnet::op::Input1 | Second input to the function |
| Cmxnet::op::OutputGrad | Gradient of output value |
| Cmxnet::op::OutputValue | Ouput value of the function to the function |
| Cmxnet::Storage::Handle | Storage handle |
| Cstd::hash< mxnet::TShape > | Hash function for TShape |
| Cstd::hash< mxnet::Tuple< T > > | Hash function for Tuple |
| Cmxnet::Imperative | Runtime functions for NDArray |
| Cmxnet::common::random::RandGenerator< cpu, DType >::Impl | |
| Cmxnet::common::random::RandGenerator< gpu, DType >::Impl | |
| Cmxnet::common::random::RandGenerator< gpu, double >::Impl | |
| ►Cmxnet::cpp::Initializer | |
| Cmxnet::cpp::Bilinear | |
| ►Cmxnet::cpp::Constant | |
| Cmxnet::cpp::One | |
| Cmxnet::cpp::Zero | |
| Cmxnet::cpp::Normal | |
| Cmxnet::cpp::Uniform | |
| ►Cmxnet::cpp::Xavier | |
| Cmxnet::cpp::MSRAPrelu | |
| Cmxnet::KVStore | Distributed key-value store |
| Cmxnet::cpp::KVStore | |
| Cmxnet::common::LazyAllocArray< TElem > | |
| CLibFeature | |
| Cmxnet::features::LibInfo | |
| ►Cmxnet::cpp::LRScheduler | Lr scheduler interface |
| Cmxnet::cpp::FactorScheduler | |
| Cmkldnn_batch_normalization_desc_t | |
| Cmkldnn_blocking_desc_t | |
| Cmkldnn_convolution_desc_t | |
| Cmkldnn_eltwise_desc_t | |
| Cmkldnn_engine | An opaque structure to describe an engine |
| Cmkldnn_inner_product_desc_t | |
| Cmkldnn_lrn_desc_t | |
| Cmkldnn_memory_desc_t | |
| Cmkldnn_pooling_desc_t | |
| Cmkldnn_post_ops | An opaque structure for a chain of post operations |
| Cmkldnn_primitive | |
| Cmkldnn_primitive_at_t | |
| Cmkldnn_primitive_attr | An opaque structure for primitive descriptor attributes |
| Cmkldnn_primitive_desc | An opaque structure to describe a primitive descriptor |
| Cmkldnn_primitive_desc_iterator | An opaque structure to describe a primitive descriptor iterator |
| Cmkldnn_rnn_cell_desc_t | |
| Cmkldnn_rnn_desc_t | |
| Cmkldnn_rnn_packed_desc_t | |
| Cmkldnn_shuffle_desc_t | |
| Cmkldnn_softmax_desc_t | |
| Cmkldnn_stream | |
| Cmkldnn_version_t | |
| Cmkldnn_wino_desc_t | |
| Cmxnet::cpp::Monitor | Monitor interface |
| CMXCallbackList | |
| Cmxnet::cpp::MXDataIterBlob | |
| Cmxnet::cpp::MXDataIterMap | |
| CNativeOpInfo | |
| Cmxnet::NDArray | Ndarray interface |
| Cmxnet::cpp::NDArray | NDArray interface |
| CNDArrayOpInfo | |
| Cmxnet::cpp::NDBlob | Struct to store NDArrayHandle |
| Cmxnet::common::ObjectPool< T > | Object pool for fast allocation and deallocation |
| Cmxnet::common::ObjectPoolAllocatable< T > | Helper trait class for easy allocation and deallocation |
| Cmxnet::OpContext | All the possible information needed by Operator.Forward and Backward This is the superset of RunContext. We use this data structure to bookkeep everything needed by Forward and Backward |
| Cmxnet::cpp::Operator | Operator interface |
| Cmxnet::Operator | Operator interface. Operator defines basic operation unit of optimized computation graph in mxnet. This interface relies on pre-allocated memory in TBlob, the caller need to set the memory region in TBlob correctly before calling Forward and Backward |
| Cmxnet::OperatorProperty | OperatorProperty is a object that stores all information about Operator. It also contains method to generate context(device) specific operators |
| Cmxnet::cpp::OpMap | OpMap instance holds a map of all the symbol creators so we can get symbol creators by name. This is used internally by Symbol and Operator |
| Cmxnet::OpStatePtr | Operator state. This is a pointer type, its content is mutable even if OpStatePtr is const |
| ►Cmxnet::cpp::Optimizer | Optimizer interface |
| Cmxnet::cpp::AdaDeltaOptimizer | |
| Cmxnet::cpp::AdaGradOptimizer | |
| Cmxnet::cpp::AdamOptimizer | |
| Cmxnet::cpp::RMSPropOptimizer | |
| Cmxnet::cpp::SGDOptimizer | |
| Cmxnet::cpp::SignumOptimizer | |
| Cmxnet::cpp::OptimizerRegistry | |
| Cmxnet::common::random::RandGenerator< Device, MSHADOW_DEFAULT_DTYPE > | |
| Cmxnet::common::random::RandGenerator< cpu, DType > | |
| Cmxnet::common::random::RandGenerator< gpu, double > | |
| Cmxnet::common::random::RandGenerator< gpu, DType > | |
| Cmxnet::Resource | Resources used by mxnet operations. A resource is something special other than NDArray, but will still participate |
| Cmxnet::ResourceManager | Global resource manager |
| Cmxnet::ResourceRequest | The resources that can be requested by Operator |
| Cmxnet::common::rsp_idx_check | Indices of RSPNDArray should be non-negative, less than the size of first dimension and in ascending order |
| Cmxnet::RunContext | Execution time context. The information needed in runtime for actual execution |
| Cmxnet::cpp::Shape | Dynamic shape class that can hold shape of arbirary dimension |
| Cmxnet::op::SimpleOpRegEntry | Registry entry to register simple operators via functions |
| Cmxnet::op::SimpleOpRegistry | Registry for TBlob functions |
| Cmxnet::common::StaticArray< T, num > | Static array. This code is borrowed from struct Shape<ndim>, except that users can specify the type of the elements of the statically allocated array. The object instance of the struct is copyable between CPU and GPU |
| Cmxnet::Storage | Storage manager across multiple devices |
| Cmxnet::cpp::SymBlob | Struct to store SymbolHandle |
| Cmxnet::cpp::Symbol | Symbol interface |
| Cmxnet::SyncedGPUAuxStream | Provides automatic coordination of an auxilary stream with a primary one. This object, upon construction, prepares an aux stream for use by syncing it with enqueued primary-stream work. Object destruction will sync again so future primary-stream work will wait on enqueued aux-stream work. If MXNET_GPU_WORKER_NSTREAMS == 1, then this defaults simply: the primary stream will equal the aux stream and the syncs will be executed as nops. See ./src/operator/cudnn/cudnn_convolution-inl.h for a usage example |
| Cmxnet::TBlob | Tensor blob class that can be used to hold tensor of any dimension, any device and any data type, This is a weak type that can be used to transfer data through interface TBlob itself do not involve any arithmentic operations, but it can be converted to tensor of fixed dimension for further operations |
| Cmxnet::Tuple< ValueType > | A dynamic sized array data structure that is optimized for storing small number of elements with same type |
| ►Cmxnet::Tuple< dim_t > | |
| Cmxnet::TShape | A Shape class that is used to represent shape of each tensor |
| Cdmlc::type_name_helper< mxnet::Tuple< T > > | |
| Cmxnet::common::helper::UniqueIf< T > | Helper for non-array type T |
| Cmxnet::common::helper::UniqueIf< T[]> | Helper for an array of unknown bound T |
| Cmxnet::common::helper::UniqueIf< T[kSize]> | Helper for an array of known bound T |
| Cmxnet::engine::Var | Base class of engine variables |
1.8.11
