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`.