mindspore.ops.LogUniformCandidateSampler

class mindspore.ops.LogUniformCandidateSampler(num_true=1, num_sampled=5, unique=True, range_max=5, seed=0)[source]

Generates random labels with a log-uniform distribution for sampled_candidates.

Randomly samples a tensor of sampled classes from the range of integers [0, range_max).

Refer to mindspore.ops.log_uniform_candidate_sampler() for more details.

Supported Platforms:: Ascend CPU

Examples

>>> sampler = ops.LogUniformCandidateSampler(2, 5, True, 5)
>>> output1, output2, output3 = sampler(Tensor(np.array([[1, 7], [0, 4], [3, 3]])))
>>> print(output1, output2, output3)
[3 2 0 4 1]
[[0.92312991 0.49336370]
 [0.99248987 0.65806371]
 [0.73553443 0.73553443]]
[0.73553443 0.82625800 0.99248987 0.65806371 0.92312991]