Add ShotNoise CPU and GPU operators #2861
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Signed-off-by: Joaquin Anton <janton@nvidia.com>
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mzient
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Apr 22, 2021
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| output[i] = denormalize(poisson_dist(normalize(input[:]) * peak) / peak) | ||
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| where ``normalize`` and ``denormalize`` represent scaling to the range [-1, 1] and back to |
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Poisson noise is unsigned - if so, then why do we have the [-1,1] range? Also - do we want to do something with negative values? (e.g. produce a noisy value from the absolute and copysign?).
mzient
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Apr 22, 2021
| DALI_HOST_DEV inline T operator()(T in_val, Generator& g) { | ||
| float norm = ConvertNorm<float>(in_val); | ||
| Dist dist(peak_ * norm); | ||
| return ConvertSatNorm<T>(dist(g) / peak_); |
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Store the reciprocal and multiply here.
Suggested change
| return ConvertSatNorm<T>(dist(g) / peak_); | |
| return ConvertSatNorm<T>(dist(g) * ipeak_); |
mzient
reviewed
Apr 22, 2021
| std::poisson_distribution<uint32_t>>; | ||
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| DALI_HOST_DEV explicit shot_noise_impl(float peak = 12) | ||
| : peak_{peak} {} |
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| : peak_{peak} {} | |
| : peak_(peak), ipeak(1/peak) {} |
Nitpick: following my advisor's recommendation - I think that such simple initialization can be expressed more naturally by plain assignment.
Signed-off-by: Joaquin Anton <janton@nvidia.com>
mzient
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Apr 22, 2021
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| The factor can be interpreted as the number of event registrations (modeled by the poisson distribution) | ||
| are required to increase the output value by 1. For example, a factor of 0.1 means we need the | ||
| 10 events to increase the output by 1, while a factor of 10 means that a single event | ||
| increases the output by 10. The higher the factor, the more noise will be applied to the data. | ||
| A factor of 0 translates to an identity operation. |
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The description is inaccurate (it's for the 1/factor). Also, perhaps we should define what a shot noise is?
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| The factor can be interpreted as the number of event registrations (modeled by the poisson distribution) | |
| are required to increase the output value by 1. For example, a factor of 0.1 means we need the | |
| 10 events to increase the output by 1, while a factor of 10 means that a single event | |
| increases the output by 10. The higher the factor, the more noise will be applied to the data. | |
| A factor of 0 translates to an identity operation. | |
| Shot noise is a noise that's 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 each 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. |
Optionally, we can add a line saying that
The values in the input must be of the same sign as the factor.
but I'm not sure if we really need to write that - an inquisitive reader should discover that on their own.
Signed-off-by: Joaquin Anton <janton@nvidia.com>
Signed-off-by: Joaquin Anton <janton@nvidia.com>
mzient
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Apr 23, 2021
banasraf
approved these changes
Apr 23, 2021
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!build |
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CI MESSAGE: [2299238]: BUILD STARTED |
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CI MESSAGE: [2299238]: BUILD PASSED |
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Signed-off-by: Joaquin Anton janton@nvidia.com
Why we need this PR?
Pick one, remove the rest
What happened in this PR?
Fill relevant points, put NA otherwise. Replace anything inside []
Implemented
noise.shotbased on the existing template for noise generators.New functionality
All
Tests added
Docstr
JIRA TASK: [DALI-1946] [DALI-1947]