File List
Here is a list of all files with brief descriptions:
[detail level 1234567]
 dot_engine-inl.hDefinitions of how Matrix Multiplications can be evaluated
 expr_engine-inl.hDefinitions of how expressions should be evaluated
 expr_scalar-inl.hDefinitions of operators in expression with respect to scalar this file will be included several times, each time with MACRO MSHADOW_SCALAR_ to be different types
 expression.hDefinitions of abstract expressions and expressions template
 extension.hSome extension of expressions, used to support something beyond elementwise op
 half.hDefinition of half (float16) type
 half2.hDefinition of vector float16, half2 type
 packet-inl.hGeneric packet vectorization code
 random.hRandom inline functions for tensor
 stream_gpu-inl.hImplementation of GPU code
 tensor_container.hTensor container that does memory allocation and resize like STL
 tensor_cpu-inl.hImplementation of CPU host code
 tensor_gpu-inl.hImplementation of GPU host code
 contrib.hUtility function to enable some contrib features
 initializer.hRandom initializer
 lr_scheduler.hScheduling learning rate
 model.hMXNET.cpp model module
 monitor.hMonitor definition
 MxNetCpp.hMeta include file for mxnet.cpp
 op_map.hDefinition of OpMap
 op_suppl.hA supplement and amendment of the operators from op.h
 op_util.hOperator helper functions
 optimizer.hDefinition of optimizer
 shape.hDefinition of shape
 symbol.hDefinition of symbol
 c_api_error.hError handling for C API
 c_api_test.hC API of mxnet for ease of testing backend in Python
 c_predict_api.hC predict API of mxnet, contains a minimum API to run prediction. This file is self-contained, and do not dependent on any other files
 engine.hEngine that schedules all the operations according to dependency
 lib_api.hAPIs to interact with libraries
 libinfo.hGet features of the MXNet library at runtime
 operator_util.hUtility functions and registries to help quickly build new operators. [Deprecated] Use the register functions in this file when possible to simplify operator creations. Operators registered in this file will be exposed to both NDArray API and symbolic API
 random_generator.hParallel random number generator
 resource.hGlobal resource allocation handling
 storage.hStorage manager across multiple devices
 tensor_blob.hTBlob class that holds common representation of arbirary dimension tensor, can be used to transformed to normal fixed dimenson tensor
 tuple.hData structure Tuple and TShape to store dynamic sized shapes
 cuda_utils.hCommon CUDA utilities
 exec_utils.hCommon utility functions for executors
 lazy_alloc_array.hAn array that lazily allocate elements as First time the cell get visited
 tensor_inspector.hUtility to inspect tensor objects
 utils.hBasic utilility functions