nvidia.dali.experimental.dynamic.random.beta#

nvidia.dali.experimental.dynamic.random.beta(shape_like=None, /, *, batch_size=None, device=None, alpha=None, beta=None, dtype=None, seed=None, shape=None, rng=None)#

Generates a random number from [0, 1] range following the beta distribution.

The beta distribution has the following probabilty distribution function:

\[f(x) = \frac{\Gamma(\alpha + \beta)}{\Gamma(\alpha)\Gamma(\beta)} x^{\alpha-1} (1-x)^{\beta-1}\]

where Г is the gamma function defined as:

\[\Gamma(\alpha) = \int_0^\infty x^{\alpha-1} e^{-x} \, dx\]

The operator supports float32 and float64 output types.

The shape of the generated data can be either specified explicitly with a shape argument, or chosen to match the shape of the __shape_like input, if provided. If none are present, a single value per sample is generated.

Supported backends

  • ‘cpu’

Parameters:

shape_like (Tensor/Batch, optional) – Shape of this input will be used to infer the shape of the output, if provided.

Keyword Arguments:

  • alpha (float or Tensor/Batch of float, optional, default = 1.0) – The alpha parameter, a positive float32 scalar.

  • beta (float or Tensor/Batch of float, optional, default = 1.0) – The beta parameter, a positive float32 scalar.

  • dtype (nvidia.dali.types.DALIDataType, optional) –

    Output data type.

    Note

    The generated numbers are converted to the output data type, rounding and clamping if necessary.

  • shape (int or list of int or Tensor/Batch of int, optional) – Shape of the output data.

  • rng (RNG, optional) – A random number generator instance. Can be obtained by calling nvidia.dali.experimental.dynamic.random.RNG(seed)(). If not provided, the default RNG is used.

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