op.h File Reference

definition of all the operators More...

#include <string>
#include <vector>
#include "mxnet-cpp/base.h"
#include "mxnet-cpp/shape.h"
#include "mxnet-cpp/op_util.h"
#include "mxnet-cpp/operator.h"
#include "dmlc/optional.h"

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Namespaces
	mxnet
	namespace of mxnet
	mxnet::cpp

Enumerations
enum	mxnet::cpp::Sample_multinomialDtype { mxnet::cpp::Sample_multinomialDtype::kInt32 = 0 }
enum	mxnet::cpp::Sample_uniformDtype { mxnet::cpp::Sample_uniformDtype::kNone = 0, mxnet::cpp::Sample_uniformDtype::kFloat16 = 1, mxnet::cpp::Sample_uniformDtype::kFloat32 = 2, mxnet::cpp::Sample_uniformDtype::kFloat64 = 3 }
enum	mxnet::cpp::Sample_normalDtype { mxnet::cpp::Sample_normalDtype::kNone = 0, mxnet::cpp::Sample_normalDtype::kFloat16 = 1, mxnet::cpp::Sample_normalDtype::kFloat32 = 2, mxnet::cpp::Sample_normalDtype::kFloat64 = 3 }
enum	mxnet::cpp::Sample_gammaDtype { mxnet::cpp::Sample_gammaDtype::kNone = 0, mxnet::cpp::Sample_gammaDtype::kFloat16 = 1, mxnet::cpp::Sample_gammaDtype::kFloat32 = 2, mxnet::cpp::Sample_gammaDtype::kFloat64 = 3 }
enum	mxnet::cpp::Sample_exponentialDtype { mxnet::cpp::Sample_exponentialDtype::kNone = 0, mxnet::cpp::Sample_exponentialDtype::kFloat16 = 1, mxnet::cpp::Sample_exponentialDtype::kFloat32 = 2, mxnet::cpp::Sample_exponentialDtype::kFloat64 = 3 }
enum	mxnet::cpp::Sample_poissonDtype { mxnet::cpp::Sample_poissonDtype::kNone = 0, mxnet::cpp::Sample_poissonDtype::kFloat16 = 1, mxnet::cpp::Sample_poissonDtype::kFloat32 = 2, mxnet::cpp::Sample_poissonDtype::kFloat64 = 3 }
enum	mxnet::cpp::Sample_negative_binomialDtype { mxnet::cpp::Sample_negative_binomialDtype::kNone = 0, mxnet::cpp::Sample_negative_binomialDtype::kFloat16 = 1, mxnet::cpp::Sample_negative_binomialDtype::kFloat32 = 2, mxnet::cpp::Sample_negative_binomialDtype::kFloat64 = 3 }
enum	mxnet::cpp::Sample_generalized_negative_binomialDtype { mxnet::cpp::Sample_generalized_negative_binomialDtype::kNone = 0, mxnet::cpp::Sample_generalized_negative_binomialDtype::kFloat16 = 1, mxnet::cpp::Sample_generalized_negative_binomialDtype::kFloat32 = 2, mxnet::cpp::Sample_generalized_negative_binomialDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_uniformDtype { mxnet::cpp::Random_uniformDtype::kNone = 0, mxnet::cpp::Random_uniformDtype::kFloat16 = 1, mxnet::cpp::Random_uniformDtype::kFloat32 = 2, mxnet::cpp::Random_uniformDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_normalDtype { mxnet::cpp::Random_normalDtype::kNone = 0, mxnet::cpp::Random_normalDtype::kFloat16 = 1, mxnet::cpp::Random_normalDtype::kFloat32 = 2, mxnet::cpp::Random_normalDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_gammaDtype { mxnet::cpp::Random_gammaDtype::kNone = 0, mxnet::cpp::Random_gammaDtype::kFloat16 = 1, mxnet::cpp::Random_gammaDtype::kFloat32 = 2, mxnet::cpp::Random_gammaDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_exponentialDtype { mxnet::cpp::Random_exponentialDtype::kNone = 0, mxnet::cpp::Random_exponentialDtype::kFloat16 = 1, mxnet::cpp::Random_exponentialDtype::kFloat32 = 2, mxnet::cpp::Random_exponentialDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_poissonDtype { mxnet::cpp::Random_poissonDtype::kNone = 0, mxnet::cpp::Random_poissonDtype::kFloat16 = 1, mxnet::cpp::Random_poissonDtype::kFloat32 = 2, mxnet::cpp::Random_poissonDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_negative_binomialDtype { mxnet::cpp::Random_negative_binomialDtype::kNone = 0, mxnet::cpp::Random_negative_binomialDtype::kFloat16 = 1, mxnet::cpp::Random_negative_binomialDtype::kFloat32 = 2, mxnet::cpp::Random_negative_binomialDtype::kFloat64 = 3 }
enum	mxnet::cpp::Random_generalized_negative_binomialDtype { mxnet::cpp::Random_generalized_negative_binomialDtype::kNone = 0, mxnet::cpp::Random_generalized_negative_binomialDtype::kFloat16 = 1, mxnet::cpp::Random_generalized_negative_binomialDtype::kFloat32 = 2, mxnet::cpp::Random_generalized_negative_binomialDtype::kFloat64 = 3 }
enum	mxnet::cpp::TopkRetTyp { mxnet::cpp::TopkRetTyp::kBoth = 0, mxnet::cpp::TopkRetTyp::kIndices = 1, mxnet::cpp::TopkRetTyp::kMask = 2, mxnet::cpp::TopkRetTyp::kValue = 3 }
enum	mxnet::cpp::CastDtype {   mxnet::cpp::CastDtype::kFloat16 = 0, mxnet::cpp::CastDtype::kFloat32 = 1, mxnet::cpp::CastDtype::kFloat64 = 2, mxnet::cpp::CastDtype::kInt32 = 3,   mxnet::cpp::CastDtype::kUint8 = 4 }
enum	mxnet::cpp::EmbeddingDtype {   mxnet::cpp::EmbeddingDtype::kFloat16 = 0, mxnet::cpp::EmbeddingDtype::kFloat32 = 1, mxnet::cpp::EmbeddingDtype::kFloat64 = 2, mxnet::cpp::EmbeddingDtype::kInt32 = 3,   mxnet::cpp::EmbeddingDtype::kUint8 = 4 }
enum	mxnet::cpp::TakeMode { mxnet::cpp::TakeMode::kClip = 0, mxnet::cpp::TakeMode::kRaise = 1, mxnet::cpp::TakeMode::kWrap = 2 }
enum	mxnet::cpp::One_hotDtype {   mxnet::cpp::One_hotDtype::kFloat16 = 0, mxnet::cpp::One_hotDtype::kFloat32 = 1, mxnet::cpp::One_hotDtype::kFloat64 = 2, mxnet::cpp::One_hotDtype::kInt32 = 3,   mxnet::cpp::One_hotDtype::kUint8 = 4 }
enum	mxnet::cpp::LeakyReLUActType { mxnet::cpp::LeakyReLUActType::kElu = 0, mxnet::cpp::LeakyReLUActType::kLeaky = 1, mxnet::cpp::LeakyReLUActType::kPrelu = 2, mxnet::cpp::LeakyReLUActType::kRrelu = 3 }
enum	mxnet::cpp::PadMode { mxnet::cpp::PadMode::kConstant = 0, mxnet::cpp::PadMode::kEdge = 1, mxnet::cpp::PadMode::kReflect = 2 }
enum	mxnet::cpp::UpSamplingSampleType { mxnet::cpp::UpSamplingSampleType::kBilinear = 0, mxnet::cpp::UpSamplingSampleType::kNearest = 1 }
enum	mxnet::cpp::UpSamplingMultiInputMode { mxnet::cpp::UpSamplingMultiInputMode::kConcat = 0, mxnet::cpp::UpSamplingMultiInputMode::kSum = 1 }
enum	mxnet::cpp::RNNMode { mxnet::cpp::RNNMode::kGru = 0, mxnet::cpp::RNNMode::kLstm = 1, mxnet::cpp::RNNMode::kRnn_relu = 2, mxnet::cpp::RNNMode::kRnn_tanh = 3 }
enum	mxnet::cpp::Convolution_v1CudnnTune { mxnet::cpp::Convolution_v1CudnnTune::kNone = 0, mxnet::cpp::Convolution_v1CudnnTune::kFastest = 1, mxnet::cpp::Convolution_v1CudnnTune::kLimited_workspace = 2, mxnet::cpp::Convolution_v1CudnnTune::kOff = 3 }
enum	mxnet::cpp::Convolution_v1Layout {   mxnet::cpp::Convolution_v1Layout::kNone = 0, mxnet::cpp::Convolution_v1Layout::kNCDHW = 1, mxnet::cpp::Convolution_v1Layout::kNCHW = 2, mxnet::cpp::Convolution_v1Layout::kNDHWC = 3,   mxnet::cpp::Convolution_v1Layout::kNHWC = 4 }
enum	mxnet::cpp::SpatialTransformerTransformType { mxnet::cpp::SpatialTransformerTransformType::kAffine = 0 }
enum	mxnet::cpp::SpatialTransformerSamplerType { mxnet::cpp::SpatialTransformerSamplerType::kBilinear = 0 }
enum	mxnet::cpp::DeconvolutionCudnnTune { mxnet::cpp::DeconvolutionCudnnTune::kNone = 0, mxnet::cpp::DeconvolutionCudnnTune::kFastest = 1, mxnet::cpp::DeconvolutionCudnnTune::kLimited_workspace = 2, mxnet::cpp::DeconvolutionCudnnTune::kOff = 3 }
enum	mxnet::cpp::DeconvolutionLayout {   mxnet::cpp::DeconvolutionLayout::kNone = 0, mxnet::cpp::DeconvolutionLayout::kNCDHW = 1, mxnet::cpp::DeconvolutionLayout::kNCHW = 2, mxnet::cpp::DeconvolutionLayout::kNCW = 3,   mxnet::cpp::DeconvolutionLayout::kNDHWC = 4, mxnet::cpp::DeconvolutionLayout::kNHWC = 5 }
enum	mxnet::cpp::SoftmaxOutputNormalization { mxnet::cpp::SoftmaxOutputNormalization::kBatch = 0, mxnet::cpp::SoftmaxOutputNormalization::kNull = 1, mxnet::cpp::SoftmaxOutputNormalization::kValid = 2 }
enum	mxnet::cpp::SoftmaxNormalization { mxnet::cpp::SoftmaxNormalization::kBatch = 0, mxnet::cpp::SoftmaxNormalization::kNull = 1, mxnet::cpp::SoftmaxNormalization::kValid = 2 }
enum	mxnet::cpp::L2NormalizationMode { mxnet::cpp::L2NormalizationMode::kChannel = 0, mxnet::cpp::L2NormalizationMode::kInstance = 1, mxnet::cpp::L2NormalizationMode::kSpatial = 2 }
enum	mxnet::cpp::GridGeneratorTransformType { mxnet::cpp::GridGeneratorTransformType::kAffine = 0, mxnet::cpp::GridGeneratorTransformType::kWarp = 1 }
enum	mxnet::cpp::Pooling_v1PoolType { mxnet::cpp::Pooling_v1PoolType::kAvg = 0, mxnet::cpp::Pooling_v1PoolType::kMax = 1, mxnet::cpp::Pooling_v1PoolType::kSum = 2 }
enum	mxnet::cpp::Pooling_v1PoolingConvention { mxnet::cpp::Pooling_v1PoolingConvention::kFull = 0, mxnet::cpp::Pooling_v1PoolingConvention::kValid = 1 }
enum	mxnet::cpp::ConvolutionCudnnTune { mxnet::cpp::ConvolutionCudnnTune::kNone = 0, mxnet::cpp::ConvolutionCudnnTune::kFastest = 1, mxnet::cpp::ConvolutionCudnnTune::kLimited_workspace = 2, mxnet::cpp::ConvolutionCudnnTune::kOff = 3 }
enum	mxnet::cpp::ConvolutionLayout {   mxnet::cpp::ConvolutionLayout::kNone = 0, mxnet::cpp::ConvolutionLayout::kNCDHW = 1, mxnet::cpp::ConvolutionLayout::kNCHW = 2, mxnet::cpp::ConvolutionLayout::kNCW = 3,   mxnet::cpp::ConvolutionLayout::kNDHWC = 4, mxnet::cpp::ConvolutionLayout::kNHWC = 5 }
enum	mxnet::cpp::PoolingPoolType { mxnet::cpp::PoolingPoolType::kAvg = 0, mxnet::cpp::PoolingPoolType::kMax = 1, mxnet::cpp::PoolingPoolType::kSum = 2 }
enum	mxnet::cpp::PoolingPoolingConvention { mxnet::cpp::PoolingPoolingConvention::kFull = 0, mxnet::cpp::PoolingPoolingConvention::kValid = 1 }
enum	mxnet::cpp::DropoutMode { mxnet::cpp::DropoutMode::kAlways = 0, mxnet::cpp::DropoutMode::kTraining = 1 }
enum	mxnet::cpp::ActivationActType { mxnet::cpp::ActivationActType::kRelu = 0, mxnet::cpp::ActivationActType::kSigmoid = 1, mxnet::cpp::ActivationActType::kSoftrelu = 2, mxnet::cpp::ActivationActType::kTanh = 3 }
enum	mxnet::cpp::SoftmaxActivationMode { mxnet::cpp::SoftmaxActivationMode::kChannel = 0, mxnet::cpp::SoftmaxActivationMode::kInstance = 1 }
enum	mxnet::cpp::MakeLossNormalization { mxnet::cpp::MakeLossNormalization::kBatch = 0, mxnet::cpp::MakeLossNormalization::kNull = 1, mxnet::cpp::MakeLossNormalization::kValid = 2 }

Functions
Symbol	mxnet::cpp::softmax (const std::string &symbol_name, Symbol data, int axis=-1)
Symbol	mxnet::cpp::log_softmax (const std::string &symbol_name, Symbol data, int axis=-1)
Symbol	mxnet::cpp::sample_multinomial (const std::string &symbol_name, Symbol data, Shape shape=Shape(), bool get_prob=false, Sample_multinomialDtype dtype=Sample_multinomialDtype::kInt32)
Symbol	mxnet::cpp::sample_uniform (const std::string &symbol_name, Symbol low, Symbol high, Shape shape=Shape(), Sample_uniformDtype dtype=Sample_uniformDtype::kNone)
Symbol	mxnet::cpp::sample_normal (const std::string &symbol_name, Symbol mu, Symbol sigma, Shape shape=Shape(), Sample_normalDtype dtype=Sample_normalDtype::kNone)
Symbol	mxnet::cpp::sample_gamma (const std::string &symbol_name, Symbol alpha, Symbol beta, Shape shape=Shape(), Sample_gammaDtype dtype=Sample_gammaDtype::kNone)
Symbol	mxnet::cpp::sample_exponential (const std::string &symbol_name, Symbol lam, Shape shape=Shape(), Sample_exponentialDtype dtype=Sample_exponentialDtype::kNone)
Symbol	mxnet::cpp::sample_poisson (const std::string &symbol_name, Symbol lam, Shape shape=Shape(), Sample_poissonDtype dtype=Sample_poissonDtype::kNone)
Symbol	mxnet::cpp::sample_negative_binomial (const std::string &symbol_name, Symbol k, Symbol p, Shape shape=Shape(), Sample_negative_binomialDtype dtype=Sample_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::sample_generalized_negative_binomial (const std::string &symbol_name, Symbol mu, Symbol alpha, Shape shape=Shape(), Sample_generalized_negative_binomialDtype dtype=Sample_generalized_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::random_uniform (const std::string &symbol_name, mx_float low=0, mx_float high=1, Shape shape=Shape(), const std::string &ctx="", Random_uniformDtype dtype=Random_uniformDtype::kNone)
Symbol	mxnet::cpp::random_normal (const std::string &symbol_name, mx_float loc=0, mx_float scale=1, Shape shape=Shape(), const std::string &ctx="", Random_normalDtype dtype=Random_normalDtype::kNone)
Symbol	mxnet::cpp::random_gamma (const std::string &symbol_name, mx_float alpha=1, mx_float beta=1, Shape shape=Shape(), const std::string &ctx="", Random_gammaDtype dtype=Random_gammaDtype::kNone)
Symbol	mxnet::cpp::random_exponential (const std::string &symbol_name, mx_float lam=1, Shape shape=Shape(), const std::string &ctx="", Random_exponentialDtype dtype=Random_exponentialDtype::kNone)
Symbol	mxnet::cpp::random_poisson (const std::string &symbol_name, mx_float lam=1, Shape shape=Shape(), const std::string &ctx="", Random_poissonDtype dtype=Random_poissonDtype::kNone)
Symbol	mxnet::cpp::random_negative_binomial (const std::string &symbol_name, int k=1, mx_float p=1, Shape shape=Shape(), const std::string &ctx="", Random_negative_binomialDtype dtype=Random_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::random_generalized_negative_binomial (const std::string &symbol_name, mx_float mu=1, mx_float alpha=1, Shape shape=Shape(), const std::string &ctx="", Random_generalized_negative_binomialDtype dtype=Random_generalized_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::broadcast_power (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_maximum (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_minimum (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_hypot (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::Reshape (const std::string &symbol_name, Symbol data, Shape shape=Shape(), bool reverse=false, Shape target_shape=Shape(), bool keep_highest=false)
Symbol	mxnet::cpp::Flatten (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::transpose (const std::string &symbol_name, Symbol data, Shape axes=Shape())
Symbol	mxnet::cpp::expand_dims (const std::string &symbol_name, Symbol data, int axis)
Symbol	mxnet::cpp::slice (const std::string &symbol_name, Symbol data, Shape begin, Shape end)
Symbol	mxnet::cpp::slice_axis (const std::string &symbol_name, Symbol data, int axis, int begin, dmlc::optional< int > end)
Symbol	mxnet::cpp::dot (const std::string &symbol_name, Symbol lhs, Symbol rhs, bool transpose_a=false, bool transpose_b=false)
Symbol	mxnet::cpp::batch_dot (const std::string &symbol_name, Symbol lhs, Symbol rhs, bool transpose_a=false, bool transpose_b=false)
Symbol	mxnet::cpp::clip (const std::string &symbol_name, Symbol data, mx_float a_min, mx_float a_max)
Symbol	mxnet::cpp::repeat (const std::string &symbol_name, Symbol data, int repeats, dmlc::optional< int > axis=dmlc::optional< int >())
Symbol	mxnet::cpp::tile (const std::string &symbol_name, Symbol data, Shape reps)
Symbol	mxnet::cpp::reverse (const std::string &symbol_name, Symbol data, Shape axis)
Symbol	mxnet::cpp::stack (const std::string &symbol_name, const std::vector< Symbol > &data, int num_args, int axis=0)
Symbol	mxnet::cpp::zeros_like (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::ones_like (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::broadcast_add (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_sub (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_mul (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_div (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_mod (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::add_n (const std::string &symbol_name, const std::vector< Symbol > &args)
Symbol	mxnet::cpp::argmax (const std::string &symbol_name, Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(), bool keepdims=false)
Symbol	mxnet::cpp::argmin (const std::string &symbol_name, Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(), bool keepdims=false)
Symbol	mxnet::cpp::argmax_channel (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::pick (const std::string &symbol_name, Symbol data, Symbol index, dmlc::optional< int > axis=dmlc::optional< int >(), bool keepdims=false)
Symbol	mxnet::cpp::sum (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::mean (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::prod (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::nansum (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::nanprod (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::max (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::min (const std::string &symbol_name, Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::broadcast_axis (const std::string &symbol_name, Symbol data, Shape axis=Shape(), Shape size=Shape())
Symbol	mxnet::cpp::broadcast_to (const std::string &symbol_name, Symbol data, Shape shape=Shape())
Symbol	mxnet::cpp::norm (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::topk (const std::string &symbol_name, Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(-1), int k=1, TopkRetTyp ret_typ=TopkRetTyp::kIndices, bool is_ascend=false)
Symbol	mxnet::cpp::sort (const std::string &symbol_name, Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(-1), bool is_ascend=true)
Symbol	mxnet::cpp::argsort (const std::string &symbol_name, Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(-1), bool is_ascend=true)
Symbol	mxnet::cpp::elemwise_add (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::relu (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::sigmoid (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::BlockGrad (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::make_loss (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::Cast (const std::string &symbol_name, Symbol data, CastDtype dtype)
Symbol	mxnet::cpp::negative (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::reciprocal (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::abs (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::sign (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::round (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::rint (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::ceil (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::floor (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::trunc (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::fix (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::square (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::sqrt (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::rsqrt (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::exp (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::log (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::log10 (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::log2 (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::sin (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::log1p (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::expm1 (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::cos (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::tan (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::arcsin (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::arccos (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::arctan (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::degrees (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::radians (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::sinh (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::cosh (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::tanh (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::arcsinh (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::arccosh (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::arctanh (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::gamma (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::gammaln (const std::string &symbol_name, Symbol data)
Symbol	mxnet::cpp::Embedding (const std::string &symbol_name, Symbol data, Symbol weight, int input_dim, int output_dim, EmbeddingDtype dtype=EmbeddingDtype::kFloat32)
Symbol	mxnet::cpp::take (const std::string &symbol_name, Symbol a, Symbol indices, int axis=0, TakeMode mode=TakeMode::kClip)
Symbol	mxnet::cpp::batch_take (const std::string &symbol_name, Symbol a, Symbol indices)
Symbol	mxnet::cpp::one_hot (const std::string &symbol_name, Symbol indices, int depth, double on_value=1, double off_value=0, One_hotDtype dtype=One_hotDtype::kFloat32)
Symbol	mxnet::cpp::broadcast_equal (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_not_equal (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_greater (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_greater_equal (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_lesser (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_lesser_equal (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::linalg_gemm (const std::string &symbol_name, Symbol A, Symbol B, Symbol C, bool transpose_a=false, bool transpose_b=false, double alpha=1, double beta=1)
Symbol	mxnet::cpp::linalg_gemm2 (const std::string &symbol_name, Symbol A, Symbol B, bool transpose_a=false, bool transpose_b=false, double alpha=1)
Symbol	mxnet::cpp::linalg_potrf (const std::string &symbol_name, Symbol A)
Symbol	mxnet::cpp::linalg_potri (const std::string &symbol_name, Symbol A)
Symbol	mxnet::cpp::linalg_trmm (const std::string &symbol_name, Symbol A, Symbol B, bool transpose=false, bool rightside=false, double alpha=1)
Symbol	mxnet::cpp::linalg_trsm (const std::string &symbol_name, Symbol A, Symbol B, bool transpose=false, bool rightside=false, double alpha=1)
Symbol	mxnet::cpp::linalg_sumlogdiag (const std::string &symbol_name, Symbol A)
Symbol	mxnet::cpp::where (const std::string &symbol_name, Symbol condition, Symbol x, Symbol y)
Symbol	mxnet::cpp::smooth_l1 (const std::string &symbol_name, Symbol data, mx_float scalar)
Symbol	mxnet::cpp::Custom (const std::string &symbol_name, const std::vector< Symbol > &data, const std::string &op_type)
Symbol	mxnet::cpp::SwapAxis (const std::string &symbol_name, Symbol data, uint32_t dim1=0, uint32_t dim2=0)
Symbol	mxnet::cpp::LeakyReLU (const std::string &symbol_name, Symbol data, LeakyReLUActType act_type=LeakyReLUActType::kLeaky, mx_float slope=0.25, mx_float lower_bound=0.125, mx_float upper_bound=0.334)
Symbol	mxnet::cpp::BatchNorm_v1 (const std::string &symbol_name, Symbol data, Symbol gamma, Symbol beta, mx_float eps=0.001, mx_float momentum=0.9, bool fix_gamma=true, bool use_global_stats=false, bool output_mean_var=false)
Symbol	mxnet::cpp::Concat (const std::string &symbol_name, const std::vector< Symbol > &data, int num_args, int dim=1)
Symbol	mxnet::cpp::sgd_update (const std::string &symbol_name, Symbol weight, Symbol grad, mx_float lr, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::sgd_mom_update (const std::string &symbol_name, Symbol weight, Symbol grad, Symbol mom, mx_float lr, mx_float momentum=0, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::mp_sgd_update (const std::string &symbol_name, Symbol weight, Symbol grad, Symbol weight32, mx_float lr, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::mp_sgd_mom_update (const std::string &symbol_name, Symbol weight, Symbol grad, Symbol mom, Symbol weight32, mx_float lr, mx_float momentum=0, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::adam_update (const std::string &symbol_name, Symbol weight, Symbol grad, Symbol mean, Symbol var, mx_float lr, mx_float beta1=0.9, mx_float beta2=0.999, mx_float epsilon=1e-08, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::rmsprop_update (const std::string &symbol_name, Symbol weight, Symbol grad, Symbol n, mx_float lr, mx_float gamma1=0.95, mx_float epsilon=1e-08, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1, mx_float clip_weights=-1)
Symbol	mxnet::cpp::rmspropalex_update (const std::string &symbol_name, Symbol weight, Symbol grad, Symbol n, Symbol g, Symbol delta, mx_float lr, mx_float gamma1=0.95, mx_float gamma2=0.9, mx_float epsilon=1e-08, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1, mx_float clip_weights=-1)
Symbol	mxnet::cpp::Pad (const std::string &symbol_name, Symbol data, PadMode mode, Shape pad_width, double constant_value=0)
Symbol	mxnet::cpp::IdentityAttachKLSparseReg (const std::string &symbol_name, Symbol data, mx_float sparseness_target=0.1, mx_float penalty=0.001, mx_float momentum=0.9)
Symbol	mxnet::cpp::SliceChannel (const std::string &symbol_name, Symbol data, int num_outputs, int axis=1, bool squeeze_axis=false)
Symbol	mxnet::cpp::softmax_cross_entropy (const std::string &symbol_name, Symbol data, Symbol label)
Symbol	mxnet::cpp::UpSampling (const std::string &symbol_name, const std::vector< Symbol > &data, uint32_t scale, UpSamplingSampleType sample_type, int num_args, uint32_t num_filter=0, UpSamplingMultiInputMode multi_input_mode=UpSamplingMultiInputMode::kConcat, uint64_t workspace=512)
Symbol	mxnet::cpp::BatchNorm (const std::string &symbol_name, Symbol data, Symbol gamma, Symbol beta, Symbol moving_mean, Symbol moving_var, double eps=0.001, mx_float momentum=0.9, bool fix_gamma=true, bool use_global_stats=false, bool output_mean_var=false, int axis=1, bool cudnn_off=false)
Symbol	mxnet::cpp::InstanceNorm (const std::string &symbol_name, Symbol data, Symbol gamma, Symbol beta, mx_float eps=0.001)
Symbol	mxnet::cpp::RNN (const std::string &symbol_name, Symbol data, Symbol parameters, Symbol state, Symbol state_cell, uint32_t state_size, uint32_t num_layers, RNNMode mode, bool bidirectional=false, mx_float p=0, bool state_outputs=false)
Symbol	mxnet::cpp::Convolution_v1 (const std::string &symbol_name, Symbol data, Symbol weight, Symbol bias, Shape kernel, uint32_t num_filter, Shape stride=Shape(), Shape dilate=Shape(), Shape pad=Shape(), uint32_t num_group=1, uint64_t workspace=1024, bool no_bias=false, Convolution_v1CudnnTune cudnn_tune=Convolution_v1CudnnTune::kNone, bool cudnn_off=false, Convolution_v1Layout layout=Convolution_v1Layout::kNone)
Symbol	mxnet::cpp::Crop (const std::string &symbol_name, const std::vector< Symbol > &data, int num_args, Shape offset=Shape(0, 0), Shape h_w=Shape(0, 0), bool center_crop=false)
Symbol	mxnet::cpp::SpatialTransformer (const std::string &symbol_name, Symbol data, Symbol loc, SpatialTransformerTransformType transform_type, SpatialTransformerSamplerType sampler_type, Shape target_shape=Shape(0, 0))
Symbol	mxnet::cpp::Deconvolution (const std::string &symbol_name, Symbol data, Symbol weight, Symbol bias, Shape kernel, uint32_t num_filter, Shape stride=Shape(), Shape dilate=Shape(), Shape pad=Shape(), Shape adj=Shape(), Shape target_shape=Shape(), uint32_t num_group=1, uint64_t workspace=512, bool no_bias=true, DeconvolutionCudnnTune cudnn_tune=DeconvolutionCudnnTune::kNone, bool cudnn_off=false, DeconvolutionLayout layout=DeconvolutionLayout::kNone)
Symbol	mxnet::cpp::SoftmaxOutput (const std::string &symbol_name, Symbol data, Symbol label, mx_float grad_scale=1, mx_float ignore_label=-1, bool multi_output=false, bool use_ignore=false, bool preserve_shape=false, SoftmaxOutputNormalization normalization=SoftmaxOutputNormalization::kNull, bool out_grad=false)
Symbol	mxnet::cpp::Softmax (const std::string &symbol_name, Symbol data, mx_float grad_scale=1, mx_float ignore_label=-1, bool multi_output=false, bool use_ignore=false, bool preserve_shape=false, SoftmaxNormalization normalization=SoftmaxNormalization::kNull, bool out_grad=false)
Symbol	mxnet::cpp::SequenceReverse (const std::string &symbol_name, Symbol data, Symbol sequence_length, bool use_sequence_length=false)
Symbol	mxnet::cpp::SequenceLast (const std::string &symbol_name, Symbol data, Symbol sequence_length, bool use_sequence_length=false)
Symbol	mxnet::cpp::Correlation (const std::string &symbol_name, Symbol data1, Symbol data2, uint32_t kernel_size=1, uint32_t max_displacement=1, uint32_t stride1=1, uint32_t stride2=1, uint32_t pad_size=0, bool is_multiply=true)
Symbol	mxnet::cpp::SVMOutput (const std::string &symbol_name, Symbol data, Symbol label, mx_float margin=1, mx_float regularization_coefficient=1, bool use_linear=false)
Symbol	mxnet::cpp::L2Normalization (const std::string &symbol_name, Symbol data, mx_float eps=1e-10, L2NormalizationMode mode=L2NormalizationMode::kInstance)
Symbol	mxnet::cpp::LRN (const std::string &symbol_name, Symbol data, uint32_t nsize, mx_float alpha=0.0001, mx_float beta=0.75, mx_float knorm=2)
Symbol	mxnet::cpp::FullyConnected (const std::string &symbol_name, Symbol data, Symbol weight, Symbol bias, int num_hidden, bool no_bias=false)
Symbol	mxnet::cpp::SequenceMask (const std::string &symbol_name, Symbol data, Symbol sequence_length, bool use_sequence_length=false, mx_float value=0)
Symbol	mxnet::cpp::GridGenerator (const std::string &symbol_name, Symbol data, GridGeneratorTransformType transform_type, Shape target_shape=Shape(0, 0))
Symbol	mxnet::cpp::Pooling_v1 (const std::string &symbol_name, Symbol data, Shape kernel, Pooling_v1PoolType pool_type, bool global_pool=false, Pooling_v1PoolingConvention pooling_convention=Pooling_v1PoolingConvention::kValid, Shape stride=Shape(), Shape pad=Shape())
Symbol	mxnet::cpp::Convolution (const std::string &symbol_name, Symbol data, Symbol weight, Symbol bias, Shape kernel, uint32_t num_filter, Shape stride=Shape(), Shape dilate=Shape(), Shape pad=Shape(), uint32_t num_group=1, uint64_t workspace=1024, bool no_bias=false, ConvolutionCudnnTune cudnn_tune=ConvolutionCudnnTune::kNone, bool cudnn_off=false, ConvolutionLayout layout=ConvolutionLayout::kNone)
Symbol	mxnet::cpp::BilinearSampler (const std::string &symbol_name, Symbol data, Symbol grid)
Symbol	mxnet::cpp::Pooling (const std::string &symbol_name, Symbol data, Shape kernel, PoolingPoolType pool_type, bool global_pool=false, bool cudnn_off=false, PoolingPoolingConvention pooling_convention=PoolingPoolingConvention::kValid, Shape stride=Shape(), Shape pad=Shape())
Symbol	mxnet::cpp::Dropout (const std::string &symbol_name, Symbol data, mx_float p=0.5, DropoutMode mode=DropoutMode::kTraining)
Symbol	mxnet::cpp::Activation (const std::string &symbol_name, Symbol data, ActivationActType act_type)
Symbol	mxnet::cpp::ROIPooling (const std::string &symbol_name, Symbol data, Symbol rois, Shape pooled_size, mx_float spatial_scale)
Symbol	mxnet::cpp::LinearRegressionOutput (const std::string &symbol_name, Symbol data, Symbol label, mx_float grad_scale=1)
Symbol	mxnet::cpp::MAERegressionOutput (const std::string &symbol_name, Symbol data, Symbol label, mx_float grad_scale=1)
Symbol	mxnet::cpp::LogisticRegressionOutput (const std::string &symbol_name, Symbol data, Symbol label, mx_float grad_scale=1)
Symbol	mxnet::cpp::SoftmaxActivation (const std::string &symbol_name, Symbol data, SoftmaxActivationMode mode=SoftmaxActivationMode::kInstance)
Symbol	mxnet::cpp::MakeLoss (const std::string &symbol_name, Symbol data, mx_float grad_scale=1, mx_float valid_thresh=0, MakeLossNormalization normalization=MakeLossNormalization::kNull)
Symbol	mxnet::cpp::choose_element_0index (const std::string &symbol_name, Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::fill_element_0index (const std::string &symbol_name, Symbol lhs, Symbol mhs, Symbol rhs)
Symbol	mxnet::cpp::softmax (Symbol data, int axis=-1)
Symbol	mxnet::cpp::log_softmax (Symbol data, int axis=-1)
Symbol	mxnet::cpp::sample_multinomial (Symbol data, Shape shape=Shape(), bool get_prob=false, Sample_multinomialDtype dtype=Sample_multinomialDtype::kInt32)
Symbol	mxnet::cpp::sample_uniform (Symbol low, Symbol high, Shape shape=Shape(), Sample_uniformDtype dtype=Sample_uniformDtype::kNone)
Symbol	mxnet::cpp::sample_normal (Symbol mu, Symbol sigma, Shape shape=Shape(), Sample_normalDtype dtype=Sample_normalDtype::kNone)
Symbol	mxnet::cpp::sample_gamma (Symbol alpha, Symbol beta, Shape shape=Shape(), Sample_gammaDtype dtype=Sample_gammaDtype::kNone)
Symbol	mxnet::cpp::sample_exponential (Symbol lam, Shape shape=Shape(), Sample_exponentialDtype dtype=Sample_exponentialDtype::kNone)
Symbol	mxnet::cpp::sample_poisson (Symbol lam, Shape shape=Shape(), Sample_poissonDtype dtype=Sample_poissonDtype::kNone)
Symbol	mxnet::cpp::sample_negative_binomial (Symbol k, Symbol p, Shape shape=Shape(), Sample_negative_binomialDtype dtype=Sample_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::sample_generalized_negative_binomial (Symbol mu, Symbol alpha, Shape shape=Shape(), Sample_generalized_negative_binomialDtype dtype=Sample_generalized_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::random_uniform (mx_float low=0, mx_float high=1, Shape shape=Shape(), const std::string &ctx="", Random_uniformDtype dtype=Random_uniformDtype::kNone)
Symbol	mxnet::cpp::random_normal (mx_float loc=0, mx_float scale=1, Shape shape=Shape(), const std::string &ctx="", Random_normalDtype dtype=Random_normalDtype::kNone)
Symbol	mxnet::cpp::random_gamma (mx_float alpha=1, mx_float beta=1, Shape shape=Shape(), const std::string &ctx="", Random_gammaDtype dtype=Random_gammaDtype::kNone)
Symbol	mxnet::cpp::random_exponential (mx_float lam=1, Shape shape=Shape(), const std::string &ctx="", Random_exponentialDtype dtype=Random_exponentialDtype::kNone)
Symbol	mxnet::cpp::random_poisson (mx_float lam=1, Shape shape=Shape(), const std::string &ctx="", Random_poissonDtype dtype=Random_poissonDtype::kNone)
Symbol	mxnet::cpp::random_negative_binomial (int k=1, mx_float p=1, Shape shape=Shape(), const std::string &ctx="", Random_negative_binomialDtype dtype=Random_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::random_generalized_negative_binomial (mx_float mu=1, mx_float alpha=1, Shape shape=Shape(), const std::string &ctx="", Random_generalized_negative_binomialDtype dtype=Random_generalized_negative_binomialDtype::kNone)
Symbol	mxnet::cpp::broadcast_power (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_maximum (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_minimum (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_hypot (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::Reshape (Symbol data, Shape shape=Shape(), bool reverse=false, Shape target_shape=Shape(), bool keep_highest=false)
Symbol	mxnet::cpp::Flatten (Symbol data)
Symbol	mxnet::cpp::transpose (Symbol data, Shape axes=Shape())
Symbol	mxnet::cpp::expand_dims (Symbol data, int axis)
Symbol	mxnet::cpp::slice (Symbol data, Shape begin, Shape end)
Symbol	mxnet::cpp::slice_axis (Symbol data, int axis, int begin, dmlc::optional< int > end)
Symbol	mxnet::cpp::dot (Symbol lhs, Symbol rhs, bool transpose_a=false, bool transpose_b=false)
Symbol	mxnet::cpp::batch_dot (Symbol lhs, Symbol rhs, bool transpose_a=false, bool transpose_b=false)
Symbol	mxnet::cpp::clip (Symbol data, mx_float a_min, mx_float a_max)
Symbol	mxnet::cpp::repeat (Symbol data, int repeats, dmlc::optional< int > axis=dmlc::optional< int >())
Symbol	mxnet::cpp::tile (Symbol data, Shape reps)
Symbol	mxnet::cpp::reverse (Symbol data, Shape axis)
Symbol	mxnet::cpp::stack (const std::vector< Symbol > &data, int num_args, int axis=0)
Symbol	mxnet::cpp::zeros_like (Symbol data)
Symbol	mxnet::cpp::ones_like (Symbol data)
Symbol	mxnet::cpp::broadcast_add (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_sub (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_mul (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_div (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_mod (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::add_n (const std::vector< Symbol > &args)
Symbol	mxnet::cpp::argmax (Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(), bool keepdims=false)
Symbol	mxnet::cpp::argmin (Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(), bool keepdims=false)
Symbol	mxnet::cpp::argmax_channel (Symbol data)
Symbol	mxnet::cpp::pick (Symbol data, Symbol index, dmlc::optional< int > axis=dmlc::optional< int >(), bool keepdims=false)
Symbol	mxnet::cpp::sum (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::mean (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::prod (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::nansum (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::nanprod (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::max (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::min (Symbol data, Shape axis=Shape(), bool keepdims=false, bool exclude=false)
Symbol	mxnet::cpp::broadcast_axis (Symbol data, Shape axis=Shape(), Shape size=Shape())
Symbol	mxnet::cpp::broadcast_to (Symbol data, Shape shape=Shape())
Symbol	mxnet::cpp::norm (Symbol data)
Symbol	mxnet::cpp::topk (Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(-1), int k=1, TopkRetTyp ret_typ=TopkRetTyp::kIndices, bool is_ascend=false)
Symbol	mxnet::cpp::sort (Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(-1), bool is_ascend=true)
Symbol	mxnet::cpp::argsort (Symbol data, dmlc::optional< int > axis=dmlc::optional< int >(-1), bool is_ascend=true)
Symbol	mxnet::cpp::elemwise_add (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::relu (Symbol data)
Symbol	mxnet::cpp::sigmoid (Symbol data)
Symbol	mxnet::cpp::BlockGrad (Symbol data)
Symbol	mxnet::cpp::make_loss (Symbol data)
Symbol	mxnet::cpp::Cast (Symbol data, CastDtype dtype)
Symbol	mxnet::cpp::negative (Symbol data)
Symbol	mxnet::cpp::reciprocal (Symbol data)
Symbol	mxnet::cpp::abs (Symbol data)
Symbol	mxnet::cpp::sign (Symbol data)
Symbol	mxnet::cpp::round (Symbol data)
Symbol	mxnet::cpp::rint (Symbol data)
Symbol	mxnet::cpp::ceil (Symbol data)
Symbol	mxnet::cpp::floor (Symbol data)
Symbol	mxnet::cpp::trunc (Symbol data)
Symbol	mxnet::cpp::fix (Symbol data)
Symbol	mxnet::cpp::square (Symbol data)
Symbol	mxnet::cpp::sqrt (Symbol data)
Symbol	mxnet::cpp::rsqrt (Symbol data)
Symbol	mxnet::cpp::exp (Symbol data)
Symbol	mxnet::cpp::log (Symbol data)
Symbol	mxnet::cpp::log10 (Symbol data)
Symbol	mxnet::cpp::log2 (Symbol data)
Symbol	mxnet::cpp::sin (Symbol data)
Symbol	mxnet::cpp::log1p (Symbol data)
Symbol	mxnet::cpp::expm1 (Symbol data)
Symbol	mxnet::cpp::cos (Symbol data)
Symbol	mxnet::cpp::tan (Symbol data)
Symbol	mxnet::cpp::arcsin (Symbol data)
Symbol	mxnet::cpp::arccos (Symbol data)
Symbol	mxnet::cpp::arctan (Symbol data)
Symbol	mxnet::cpp::degrees (Symbol data)
Symbol	mxnet::cpp::radians (Symbol data)
Symbol	mxnet::cpp::sinh (Symbol data)
Symbol	mxnet::cpp::cosh (Symbol data)
Symbol	mxnet::cpp::tanh (Symbol data)
Symbol	mxnet::cpp::arcsinh (Symbol data)
Symbol	mxnet::cpp::arccosh (Symbol data)
Symbol	mxnet::cpp::arctanh (Symbol data)
Symbol	mxnet::cpp::gamma (Symbol data)
Symbol	mxnet::cpp::gammaln (Symbol data)
Symbol	mxnet::cpp::Embedding (Symbol data, Symbol weight, int input_dim, int output_dim, EmbeddingDtype dtype=EmbeddingDtype::kFloat32)
Symbol	mxnet::cpp::take (Symbol a, Symbol indices, int axis=0, TakeMode mode=TakeMode::kClip)
Symbol	mxnet::cpp::batch_take (Symbol a, Symbol indices)
Symbol	mxnet::cpp::one_hot (Symbol indices, int depth, double on_value=1, double off_value=0, One_hotDtype dtype=One_hotDtype::kFloat32)
Symbol	mxnet::cpp::broadcast_equal (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_not_equal (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_greater (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_greater_equal (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_lesser (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::broadcast_lesser_equal (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::linalg_gemm (Symbol A, Symbol B, Symbol C, bool transpose_a=false, bool transpose_b=false, double alpha=1, double beta=1)
Symbol	mxnet::cpp::linalg_gemm2 (Symbol A, Symbol B, bool transpose_a=false, bool transpose_b=false, double alpha=1)
Symbol	mxnet::cpp::linalg_potrf (Symbol A)
Symbol	mxnet::cpp::linalg_potri (Symbol A)
Symbol	mxnet::cpp::linalg_trmm (Symbol A, Symbol B, bool transpose=false, bool rightside=false, double alpha=1)
Symbol	mxnet::cpp::linalg_trsm (Symbol A, Symbol B, bool transpose=false, bool rightside=false, double alpha=1)
Symbol	mxnet::cpp::linalg_sumlogdiag (Symbol A)
Symbol	mxnet::cpp::where (Symbol condition, Symbol x, Symbol y)
Symbol	mxnet::cpp::smooth_l1 (Symbol data, mx_float scalar)
Symbol	mxnet::cpp::Custom (const std::vector< Symbol > &data, const std::string &op_type)
Symbol	mxnet::cpp::SwapAxis (Symbol data, uint32_t dim1=0, uint32_t dim2=0)
Symbol	mxnet::cpp::LeakyReLU (Symbol data, LeakyReLUActType act_type=LeakyReLUActType::kLeaky, mx_float slope=0.25, mx_float lower_bound=0.125, mx_float upper_bound=0.334)
Symbol	mxnet::cpp::BatchNorm_v1 (Symbol data, Symbol gamma, Symbol beta, mx_float eps=0.001, mx_float momentum=0.9, bool fix_gamma=true, bool use_global_stats=false, bool output_mean_var=false)
Symbol	mxnet::cpp::Concat (const std::vector< Symbol > &data, int num_args, int dim=1)
Symbol	mxnet::cpp::sgd_update (Symbol weight, Symbol grad, mx_float lr, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::sgd_mom_update (Symbol weight, Symbol grad, Symbol mom, mx_float lr, mx_float momentum=0, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::mp_sgd_update (Symbol weight, Symbol grad, Symbol weight32, mx_float lr, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::mp_sgd_mom_update (Symbol weight, Symbol grad, Symbol mom, Symbol weight32, mx_float lr, mx_float momentum=0, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::adam_update (Symbol weight, Symbol grad, Symbol mean, Symbol var, mx_float lr, mx_float beta1=0.9, mx_float beta2=0.999, mx_float epsilon=1e-08, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1)
Symbol	mxnet::cpp::rmsprop_update (Symbol weight, Symbol grad, Symbol n, mx_float lr, mx_float gamma1=0.95, mx_float epsilon=1e-08, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1, mx_float clip_weights=-1)
Symbol	mxnet::cpp::rmspropalex_update (Symbol weight, Symbol grad, Symbol n, Symbol g, Symbol delta, mx_float lr, mx_float gamma1=0.95, mx_float gamma2=0.9, mx_float epsilon=1e-08, mx_float wd=0, mx_float rescale_grad=1, mx_float clip_gradient=-1, mx_float clip_weights=-1)
Symbol	mxnet::cpp::Pad (Symbol data, PadMode mode, Shape pad_width, double constant_value=0)
Symbol	mxnet::cpp::IdentityAttachKLSparseReg (Symbol data, mx_float sparseness_target=0.1, mx_float penalty=0.001, mx_float momentum=0.9)
Symbol	mxnet::cpp::SliceChannel (Symbol data, int num_outputs, int axis=1, bool squeeze_axis=false)
Symbol	mxnet::cpp::softmax_cross_entropy (Symbol data, Symbol label)
Symbol	mxnet::cpp::UpSampling (const std::vector< Symbol > &data, uint32_t scale, UpSamplingSampleType sample_type, int num_args, uint32_t num_filter=0, UpSamplingMultiInputMode multi_input_mode=UpSamplingMultiInputMode::kConcat, uint64_t workspace=512)
Symbol	mxnet::cpp::BatchNorm (Symbol data, Symbol gamma, Symbol beta, Symbol moving_mean, Symbol moving_var, double eps=0.001, mx_float momentum=0.9, bool fix_gamma=true, bool use_global_stats=false, bool output_mean_var=false, int axis=1, bool cudnn_off=false)
Symbol	mxnet::cpp::InstanceNorm (Symbol data, Symbol gamma, Symbol beta, mx_float eps=0.001)
Symbol	mxnet::cpp::RNN (Symbol data, Symbol parameters, Symbol state, Symbol state_cell, uint32_t state_size, uint32_t num_layers, RNNMode mode, bool bidirectional=false, mx_float p=0, bool state_outputs=false)
Symbol	mxnet::cpp::Convolution_v1 (Symbol data, Symbol weight, Symbol bias, Shape kernel, uint32_t num_filter, Shape stride=Shape(), Shape dilate=Shape(), Shape pad=Shape(), uint32_t num_group=1, uint64_t workspace=1024, bool no_bias=false, Convolution_v1CudnnTune cudnn_tune=Convolution_v1CudnnTune::kNone, bool cudnn_off=false, Convolution_v1Layout layout=Convolution_v1Layout::kNone)
Symbol	mxnet::cpp::Crop (const std::vector< Symbol > &data, int num_args, Shape offset=Shape(0, 0), Shape h_w=Shape(0, 0), bool center_crop=false)
Symbol	mxnet::cpp::SpatialTransformer (Symbol data, Symbol loc, SpatialTransformerTransformType transform_type, SpatialTransformerSamplerType sampler_type, Shape target_shape=Shape(0, 0))
Symbol	mxnet::cpp::Deconvolution (Symbol data, Symbol weight, Symbol bias, Shape kernel, uint32_t num_filter, Shape stride=Shape(), Shape dilate=Shape(), Shape pad=Shape(), Shape adj=Shape(), Shape target_shape=Shape(), uint32_t num_group=1, uint64_t workspace=512, bool no_bias=true, DeconvolutionCudnnTune cudnn_tune=DeconvolutionCudnnTune::kNone, bool cudnn_off=false, DeconvolutionLayout layout=DeconvolutionLayout::kNone)
Symbol	mxnet::cpp::SoftmaxOutput (Symbol data, Symbol label, mx_float grad_scale=1, mx_float ignore_label=-1, bool multi_output=false, bool use_ignore=false, bool preserve_shape=false, SoftmaxOutputNormalization normalization=SoftmaxOutputNormalization::kNull, bool out_grad=false)
Symbol	mxnet::cpp::Softmax (Symbol data, mx_float grad_scale=1, mx_float ignore_label=-1, bool multi_output=false, bool use_ignore=false, bool preserve_shape=false, SoftmaxNormalization normalization=SoftmaxNormalization::kNull, bool out_grad=false)
Symbol	mxnet::cpp::SequenceReverse (Symbol data, Symbol sequence_length, bool use_sequence_length=false)
Symbol	mxnet::cpp::SequenceLast (Symbol data, Symbol sequence_length, bool use_sequence_length=false)
Symbol	mxnet::cpp::Correlation (Symbol data1, Symbol data2, uint32_t kernel_size=1, uint32_t max_displacement=1, uint32_t stride1=1, uint32_t stride2=1, uint32_t pad_size=0, bool is_multiply=true)
Symbol	mxnet::cpp::SVMOutput (Symbol data, Symbol label, mx_float margin=1, mx_float regularization_coefficient=1, bool use_linear=false)
Symbol	mxnet::cpp::L2Normalization (Symbol data, mx_float eps=1e-10, L2NormalizationMode mode=L2NormalizationMode::kInstance)
Symbol	mxnet::cpp::LRN (Symbol data, uint32_t nsize, mx_float alpha=0.0001, mx_float beta=0.75, mx_float knorm=2)
Symbol	mxnet::cpp::FullyConnected (Symbol data, Symbol weight, Symbol bias, int num_hidden, bool no_bias=false)
Symbol	mxnet::cpp::SequenceMask (Symbol data, Symbol sequence_length, bool use_sequence_length=false, mx_float value=0)
Symbol	mxnet::cpp::GridGenerator (Symbol data, GridGeneratorTransformType transform_type, Shape target_shape=Shape(0, 0))
Symbol	mxnet::cpp::Pooling_v1 (Symbol data, Shape kernel, Pooling_v1PoolType pool_type, bool global_pool=false, Pooling_v1PoolingConvention pooling_convention=Pooling_v1PoolingConvention::kValid, Shape stride=Shape(), Shape pad=Shape())
Symbol	mxnet::cpp::Convolution (Symbol data, Symbol weight, Symbol bias, Shape kernel, uint32_t num_filter, Shape stride=Shape(), Shape dilate=Shape(), Shape pad=Shape(), uint32_t num_group=1, uint64_t workspace=1024, bool no_bias=false, ConvolutionCudnnTune cudnn_tune=ConvolutionCudnnTune::kNone, bool cudnn_off=false, ConvolutionLayout layout=ConvolutionLayout::kNone)
Symbol	mxnet::cpp::BilinearSampler (Symbol data, Symbol grid)
Symbol	mxnet::cpp::Pooling (Symbol data, Shape kernel, PoolingPoolType pool_type, bool global_pool=false, bool cudnn_off=false, PoolingPoolingConvention pooling_convention=PoolingPoolingConvention::kValid, Shape stride=Shape(), Shape pad=Shape())
Symbol	mxnet::cpp::Dropout (Symbol data, mx_float p=0.5, DropoutMode mode=DropoutMode::kTraining)
Symbol	mxnet::cpp::Activation (Symbol data, ActivationActType act_type)
Symbol	mxnet::cpp::ROIPooling (Symbol data, Symbol rois, Shape pooled_size, mx_float spatial_scale)
Symbol	mxnet::cpp::LinearRegressionOutput (Symbol data, Symbol label, mx_float grad_scale=1)
Symbol	mxnet::cpp::MAERegressionOutput (Symbol data, Symbol label, mx_float grad_scale=1)
Symbol	mxnet::cpp::LogisticRegressionOutput (Symbol data, Symbol label, mx_float grad_scale=1)
Symbol	mxnet::cpp::SoftmaxActivation (Symbol data, SoftmaxActivationMode mode=SoftmaxActivationMode::kInstance)
Symbol	mxnet::cpp::MakeLoss (Symbol data, mx_float grad_scale=1, mx_float valid_thresh=0, MakeLossNormalization normalization=MakeLossNormalization::kNull)
Symbol	mxnet::cpp::choose_element_0index (Symbol lhs, Symbol rhs)
Symbol	mxnet::cpp::fill_element_0index (Symbol lhs, Symbol mhs, Symbol rhs)

Detailed Description

definition of all the operators

Copyright (c) 2016 by Contributors

Author

Chuntao Hong, Xin Li