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| lrn (const primitive_id &id, const primitive_id &input, uint32_t size, float k, float alpha, float beta, cldnn_lrn_norm_region lrn_norm_region, const padding &output_padding=padding()) |
| Constructs LRN primitive. More...
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| lrn (const dto *dto) |
| Constructs a copy from C API cldnn_normalization_desc.
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const cldnn_primitive_desc * | get_dto () const override |
| Returns pointer to a C API primitive descriptor casted to cldnn_primitive_desc.
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| primitive (const primitive_type_id &type, const primitive_id &id, const std::vector< primitive_id > &input, const padding &output_padding=padding()) |
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| primitive (const cldnn_primitive_desc *dto) |
| Constructs a copy from basic C API cldnn_primitive_desc.
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std::vector< std::reference_wrapper< primitive_id > > | dependecies () |
| Returns references to all primitive ids on which this primitive depends - inputs, weights, biases, etc.
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std::vector< primitive_id > | dependecies () const |
| Returns copy of all primitive ids on which this primitive depends - inputs, weights, biases, etc.
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| operator primitive_id () const |
| Implicit conversion to primiitive id.
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Local response normalization.
LRN layer as described in chapter 3.3 of "ImageNet Classification with Deep Convolutional
Neural Networks" by Khrizevsky, Sutskever, Hinton.
See: http://www.cs.toronto.edu/~fritz/absps/imagenet.pdf
- Alogrithm:
- b(i,x,y) = a(i,x,y) / (k+alpha*sum(min(N-1, i+n/2); j=max(0,i-n/2); a(j,x,y)^2))
- Where:
- b(i,x,y) : value at x, y from i-th feature map after normalization
- a(i,x,y) : value at x, y from i-th feature map before normalization
- N : number of feature maps
- n : size of normalization
- k, alpha, beta : hyper parameters (equal to 2, 10e-4, 0.75 in paper).
Definition at line 42 of file lrn.hpp.