Table Of Contents
Table Of Contents

TripletLoss

class mxnet.gluon.loss.TripletLoss(margin=1, weight=None, batch_axis=0, **kwargs)[source]

Calculates triplet loss given three input tensors and a positive margin. Triplet loss measures the relative similarity between prediction, a positive example and a negative example:

\[L = \sum_i \max(\Vert {pred}_i - {pos_i} \Vert_2^2 - \Vert {pred}_i - {neg_i} \Vert_2^2 + {margin}, 0)\]

pred, positive and negative can have arbitrary shape as long as they have the same number of elements.

Parameters:
  • margin (float) – Margin of separation between correct and incorrect pair.
  • weight (float or None) – Global scalar weight for loss.
  • batch_axis (int, default 0) – The axis that represents mini-batch.
Inputs:
  • pred: prediction tensor with arbitrary shape
  • positive: positive example tensor with arbitrary shape. Must have the same size as pred.
  • negative: negative example tensor with arbitrary shape Must have the same size as pred.
Outputs:
  • loss: loss tensor with shape (batch_size,).
__init__(margin=1, weight=None, batch_axis=0, **kwargs)[source]

Initialize self. See help(type(self)) for accurate signature.

Methods

__init__([margin, weight, batch_axis]) Initialize self.
apply(fn) Applies fn recursively to every child block as well as self.
cast(dtype) Cast this Block to use another data type.
collect_params([select]) Returns a ParameterDict containing this Block and all of its children’s Parameters(default), also can returns the select ParameterDict which match some given regular expressions.
export(path[, epoch]) Export HybridBlock to json format that can be loaded by SymbolBlock.imports, mxnet.mod.Module or the C++ interface.
forward(x, *args) Defines the forward computation.
hybrid_forward(F, pred, positive, negative) Overrides to construct symbolic graph for this Block.
hybridize([active]) Activates or deactivates HybridBlock s recursively.
infer_shape(*args) Infers shape of Parameters from inputs.
infer_type(*args) Infers data type of Parameters from inputs.
initialize([init, ctx, verbose, force_reinit]) Initializes Parameter s of this Block and its children.
load_parameters(filename[, ctx, …]) Load parameters from file previously saved by save_parameters.
load_params(filename[, ctx, allow_missing, …]) [Deprecated] Please use load_parameters.
name_scope() Returns a name space object managing a child Block and parameter names.
register_child(block[, name]) Registers block as a child of self.
register_forward_hook(hook) Registers a forward hook on the block.
register_forward_pre_hook(hook) Registers a forward pre-hook on the block.
save_parameters(filename) Save parameters to file.
save_params(filename) [Deprecated] Please use save_parameters.
summary(*inputs) Print the summary of the model’s output and parameters.

Attributes

name Name of this Block, without ‘_’ in the end.
params Returns this Block’s parameter dictionary (does not include its children’s parameters).
prefix Prefix of this Block.