Class WeightedRandomSampler
- Defined in File samplers.h 
Inheritance Relationships
Base Type
- public mindspore::dataset::Sampler(Class Sampler)
Class Documentation
- 
class WeightedRandomSampler : public mindspore::dataset::Sampler
- A class to represent a Weighted Random Sampler in the data pipeline. - Note - Samples the elements from [0, len(weights) - 1] randomly with the given weights (probabilities). - Public Functions - 
explicit WeightedRandomSampler(const std::vector<double> &weights, int64_t num_samples = 0, bool replacement = true)
- Constructor. - Parameters
- weights – [in] A vector sequence of weights, not necessarily summing up to 1. 
- num_samples – [in] The number of samples to draw (default=0, return all samples). 
- replacement – [in] If true, put the sample ID back for the next draw (default=true). 
 样例
- /* creates a WeightedRandomSampler that will sample 4 elements without replacement */ std::vector<double> weights = {0.9, 0.8, 0.68, 0.7, 0.71, 0.6, 0.5, 0.4, 0.3, 0.5, 0.2, 0.1}; sampler = std::make_shared<WeightedRandomSampler>(weights, 4); std::string folder_path = "/path/to/image/folder"; std::shared_ptr<Dataset> ds = ImageFolder(folder_path, false, sampler); 
 
 - 
~WeightedRandomSampler() = default
- Destructor. 
 
- 
explicit WeightedRandomSampler(const std::vector<double> &weights, int64_t num_samples = 0, bool replacement = true)