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Note that a call to tfd_sample() without arguments will generate a single sample.
tfd_sample()
tfd_sample(distribution, sample_shape = list(), ...)
The distribution being used.
0D or 1D int32 Tensor. Shape of the generated samples.
Additional parameters passed to Python.
a Tensor with prepended dimensions sample_shape.
Other distribution_methods: tfd_cdf(), tfd_covariance(), tfd_cross_entropy(), tfd_entropy(), tfd_kl_divergence(), tfd_log_cdf(), tfd_log_prob(), tfd_log_survival_function(), tfd_mean(), tfd_mode(), tfd_prob(), tfd_quantile(), tfd_stddev(), tfd_survival_function(), tfd_variance()
tfd_cdf()
tfd_covariance()
tfd_cross_entropy()
tfd_entropy()
tfd_kl_divergence()
tfd_log_cdf()
tfd_log_prob()
tfd_log_survival_function()
tfd_mean()
tfd_mode()
tfd_prob()
tfd_quantile()
tfd_stddev()
tfd_survival_function()
tfd_variance()
# NOT RUN { d <- tfd_normal(loc = c(1, 2), scale = c(1, 0.5)) d %>% tfd_sample() # }
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