Buckets:
generation/logits_sampler
- generation/logits_sampler
- static
- .LogitsSampler
new LogitsSampler(generation_config)- instance
._call(logits)⇒ Promise.<Array>.sample(logits)⇒ Promise.<Array>.getLogits(logits, index)⇒ Float32Array.randomSelect(probabilities)⇒ number
- static
.getSampler(generation_config)⇒ LogitsSampler
- .LogitsSampler
- inner
- ~GreedySampler
.sample(logits)⇒ Promise.<Array>
- ~MultinomialSampler
.sample(logits)⇒ Promise.<Array>
- ~BeamSearchSampler
.sample(logits)⇒ Promise.<Array>
- ~GreedySampler
- static
generation/logits_sampler.LogitsSampler
Sampler is a base class for all sampling methods used for text generation.
Kind: static class of generation/logits_sampler
- .LogitsSampler
new LogitsSampler(generation_config)- instance
._call(logits)⇒ Promise.<Array>.sample(logits)⇒ Promise.<Array>.getLogits(logits, index)⇒ Float32Array.randomSelect(probabilities)⇒ number
- static
.getSampler(generation_config)⇒ LogitsSampler
new LogitsSampler(generation_config)
Creates a new Sampler object with the specified generation config.
ParamTypeDescription
generation_configGenerationConfigThe generation config.
logitsSampler._call(logits) ⇒ Promise.<Array>
Executes the sampler, using the specified logits.
Kind: instance method of LogitsSampler
ParamType
logitsTensor
logitsSampler.sample(logits) ⇒ Promise.<Array>
Abstract method for sampling the logits.
Kind: instance method of LogitsSampler
Throws:
Error If not implemented in subclass.
ParamTypelogitsTensor
logitsSampler.getLogits(logits, index) ⇒ Float32Array
Returns the specified logits as an array, with temperature applied.
Kind: instance method of LogitsSampler
ParamType
logitsTensor
indexnumber
logitsSampler.randomSelect(probabilities) ⇒ number
Selects an item randomly based on the specified probabilities.
Kind: instance method of LogitsSampler
Returns: number - The index of the selected item.
ParamTypeDescription
probabilitiesFloat32ArrayAn array of probabilities to use for selection.
LogitsSampler.getSampler(generation_config) ⇒ LogitsSampler
Returns a Sampler object based on the specified options.
Kind: static method of LogitsSampler
Returns: LogitsSampler - A Sampler object.
ParamTypeDescription
generation_configGenerationConfigAn object containing options for the sampler.
generation/logits_sampler~GreedySampler
Class representing a Greedy Sampler.
Kind: inner class of generation/logits_sampler
greedySampler.sample(logits) ⇒ Promise.<Array>
Sample the maximum probability of a given logits tensor.
Kind: instance method of GreedySampler
Returns: Promise.<Array> - An array with a single tuple, containing the index of the maximum value and a meaningless score (since this is a greedy search).
ParamType
logitsTensor
generation/logits_sampler~MultinomialSampler
Class representing a MultinomialSampler.
Kind: inner class of generation/logits_sampler
multinomialSampler.sample(logits) ⇒ Promise.<Array>
Sample from the logits.
Kind: instance method of MultinomialSampler
ParamType
logitsTensor
generation/logits_sampler~BeamSearchSampler
Class representing a BeamSearchSampler.
Kind: inner class of generation/logits_sampler
beamSearchSampler.sample(logits) ⇒ Promise.<Array>
Sample from the logits.
Kind: instance method of BeamSearchSampler
ParamType
logitsTensor
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