Class FakeImageDataset
Defined in File datasets.h
Inheritance Relationships
Base Type
public mindspore::dataset::Dataset
(Class Dataset)
Class Documentation
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class FakeImageDataset : public mindspore::dataset::Dataset
A source dataset for generating fake images.
Public Functions
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FakeImageDataset(int32_t num_images, const std::vector<int32_t> &image_size, int32_t num_classes, int32_t base_seed, const std::shared_ptr<Sampler> &sampler, const std::shared_ptr<DatasetCache> &cache)
Constructor of FakeImageDataset.
- Parameters
num_images – [in] The number of images to generate, which must be positive.
image_size – [in] Size of the images, which must be a vector of three positive values.
num_classes – [in] The number of classes of the images, which must be positive.
base_seed – [in] The base seed to generate the images.
sampler – [in] Shared pointer to a sampler object used to choose samples from the dataset. If sampler is not given, a
RandomSampler
will be used to randomly iterate the entire dataset.cache – [in] Tensor cache to use.
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FakeImageDataset(int32_t num_images, const std::vector<int32_t> &image_size, int32_t num_classes, int32_t base_seed, const Sampler *sampler, const std::shared_ptr<DatasetCache> &cache)
Constructor of FakeImageDataset.
- Parameters
num_images – [in] The number of images to generate, which must be positive.
image_size – [in] Size of the images, which must be a vector of three positive values.
num_classes – [in] The number of classes of the images, which must be positive.
base_seed – [in] The base seed to generate the images.
sampler – [in] Raw pointer to a sampler object used to choose samples from the dataset.
cache – [in] Tensor cache to use.
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FakeImageDataset(int32_t num_images, const std::vector<int32_t> &image_size, int32_t num_classes, int32_t base_seed, const std::reference_wrapper<Sampler> &sampler, const std::shared_ptr<DatasetCache> &cache)
Constructor of FakeImageDataset.
- Parameters
num_images – [in] The number of images to generate, which must be positive.
image_size – [in] Size of the images, which must be a vector of three positive values.
num_classes – [in] The number of classes of the images, which must be positive.
base_seed – [in] The base seed to generate the images.
sampler – [in] Sampler object used to choose samples from the dataset.
cache – [in] Tensor cache to use.
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~FakeImageDataset() override = default
Destructor of FakeImageDataset.
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FakeImageDataset(int32_t num_images, const std::vector<int32_t> &image_size, int32_t num_classes, int32_t base_seed, const std::shared_ptr<Sampler> &sampler, const std::shared_ptr<DatasetCache> &cache)