Applies shot noise to the input.
The shot noise is generated by applying the following formula:
output[:] = poisson_dist(max(0, input[:] / factor)) * factor) if factor != 0 output[:] = input[:] if factor == 0
where poisson_dist represents a poisson distribution.
Shot noise is a noise thatâs present in data generated by a Poisson process, like registering photons by an image sensor. This operator simulates the data acquisition process where each event increases the output value by factor and the input tensor contains the expected values of corresponding output points. For example, a factor of 0.1 means that 10 events are needed to increase the output value by 1, while a factor of 10 means that a single event increases the output by 10. The output values are quantized to multiples of factor. The larger the factor, the more noise is present in the output. A factor of 0 makes this an identity operation.
The shape and data type of the output will match the input.
âcpuâ
âgpuâ
__input¶ (TensorList) â Input to the operator.
bytes_per_sample_hint¶ (int or list of int, optional, default = [0]) â
Output size hint, in bytes per sample.
If specified, the operatorâs outputs residing in GPU or page-locked host memory will be preallocated to accommodate a batch of samples of this size.
factor¶ (float or TensorList of float, optional, default = 20.0) â Factor parameter.
preserve¶ (bool, optional, default = False) â Prevents the operator from being removed from the graph even if its outputs are not used.
seed¶ (int, optional, default = -1) â Random seed; if not set, one will be assigned automatically.
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