Table Of Contents
Table Of Contents

mxnet.gluon.loss.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.