class MXNet::Symbol::Contrib

Defined in:

Class Method Summary

Class Method Detail

def self._AdaptiveAvgPooling2D(data : MXNet::Symbol?, **kwargs) #

def self._backward_quadratic(**kwargs) #

def self._BilinearResize2D(data : MXNet::Symbol?, height, width, **kwargs) #

def self._bipartite_matching(data : MXNet::Symbol?, threshold, **kwargs) #

def self._box_iou(lhs : MXNet::Symbol?, rhs : MXNet::Symbol?, **kwargs) #

def self._box_nms(data : MXNet::Symbol?, **kwargs) #

def self._box_non_maximum_suppression(data : MXNet::Symbol?, **kwargs) #

def self._count_sketch(data : MXNet::Symbol?, h : MXNet::Symbol?, s : MXNet::Symbol?, out_dim, **kwargs) #

def self._ctc_loss(data : MXNet::Symbol?, label : MXNet::Symbol?, data_lengths : MXNet::Symbol?, label_lengths : MXNet::Symbol?, **kwargs) #

def self._CTCLoss(data : MXNet::Symbol?, label : MXNet::Symbol?, data_lengths : MXNet::Symbol?, label_lengths : MXNet::Symbol?, **kwargs) #

def self._DeformableConvolution(data : MXNet::Symbol?, offset : MXNet::Symbol?, weight : MXNet::Symbol?, bias : MXNet::Symbol?, kernel, num_filter, **kwargs) #

def self._DeformablePSROIPooling(spatial_scale, output_dim, group_size, pooled_size, **kwargs) #

def self._dequantize(data : MXNet::Symbol?, min_range : MXNet::Symbol?, max_range : MXNet::Symbol?, **kwargs) #

def self._div_sqrt_dim(data : MXNet::Symbol?, **kwargs) #

def self._fft(data : MXNet::Symbol?, **kwargs) #

def self._ifft(data : MXNet::Symbol?, **kwargs) #

def self._MultiBoxDetection(cls_prob : MXNet::Symbol?, loc_pred : MXNet::Symbol?, anchor : MXNet::Symbol?, **kwargs) #

def self._MultiBoxPrior(data : MXNet::Symbol?, **kwargs) #

def self._MultiBoxTarget(anchor : MXNet::Symbol?, label : MXNet::Symbol?, cls_pred : MXNet::Symbol?, **kwargs) #

def self._MultiProposal(cls_prob : MXNet::Symbol?, bbox_pred : MXNet::Symbol?, im_info : MXNet::Symbol?, **kwargs) #

def self._Proposal(cls_prob : MXNet::Symbol?, bbox_pred : MXNet::Symbol?, im_info : MXNet::Symbol?, **kwargs) #

def self._PSROIPooling(spatial_scale, output_dim, pooled_size, **kwargs) #

def self._quadratic(data : MXNet::Symbol?, **kwargs) #

def self._quantize(data : MXNet::Symbol?, min_range : MXNet::Symbol?, max_range : MXNet::Symbol?, **kwargs) #

def self._quantized_conv(data : MXNet::Symbol?, weight : MXNet::Symbol?, bias : MXNet::Symbol?, min_data : MXNet::Symbol?, max_data : MXNet::Symbol?, min_weight : MXNet::Symbol?, max_weight : MXNet::Symbol?, min_bias : MXNet::Symbol?, max_bias : MXNet::Symbol?, kernel, num_filter, **kwargs) #

def self._quantized_flatten(data : MXNet::Symbol?, min_data : MXNet::Symbol?, max_data : MXNet::Symbol?, **kwargs) #

def self._quantized_fully_connected(data : MXNet::Symbol?, weight : MXNet::Symbol?, bias : MXNet::Symbol?, min_data : MXNet::Symbol?, max_data : MXNet::Symbol?, min_weight : MXNet::Symbol?, max_weight : MXNet::Symbol?, min_bias : MXNet::Symbol?, max_bias : MXNet::Symbol?, num_hidden, **kwargs) #

def self._quantized_pooling(data : MXNet::Symbol?, min_data : MXNet::Symbol?, max_data : MXNet::Symbol?, **kwargs) #

def self._requantize(data : MXNet::Symbol?, min_range : MXNet::Symbol?, max_range : MXNet::Symbol?, **kwargs) #

def self._ROIAlign(data : MXNet::Symbol?, rois : MXNet::Symbol?, pooled_size, spatial_scale, **kwargs) #

def self._SparseEmbedding(data : MXNet::Symbol?, weight : MXNet::Symbol?, input_dim, output_dim, **kwargs) #

def self._SyncBatchNorm(data : MXNet::Symbol?, gamma : MXNet::Symbol?, beta : MXNet::Symbol?, moving_mean : MXNet::Symbol?, moving_var : MXNet::Symbol?, **kwargs) #