C++ API Reference for Intel® Data Analytics Acceleration Library 2019
Contains classes for neural network layers.
Namespaces | |
| abs | |
| Contains classes of the abs layer. | |
| average_pooling1d | |
| Contains classes for average one-dimensional (1D) pooling layer. | |
| average_pooling2d | |
| Contains classes for average two-dimensional (2D) pooling layer. | |
| average_pooling3d | |
| Contains classes for average three-dimensional (3D) pooling layer. | |
| backward | |
| Contains classes for the backward stage of the neural network layer. | |
| batch_normalization | |
| Contains classes for batch normalization layer. | |
| concat | |
| Contains classes for the concat layer. | |
| convolution2d | |
| Contains classes for neural network 2D convolution layer. | |
| dropout | |
| Contains classes for dropout layer. | |
| eltwise_sum | |
| Contains classes for neural network element-wise sum layer. | |
| elu | |
| Contains classes for the ELU layer. | |
| forward | |
| Contains classes for the forward stage of the neural network layer. | |
| fullyconnected | |
| Contains classes for neural network fully-connected layer. | |
| interface1 | |
| Contains version 1.0 of Intel(R) Data Analytics Acceleration Library (Intel(R) DAAL) interface. | |
| lcn | |
| Contains classes for neural network local contrast normalization layer. | |
| locallyconnected2d | |
| Contains classes for neural network 2D locally connected layer. | |
| logistic | |
| Contains classes for the logistic layer. | |
| loss | |
| Contains classes for loss layer. | |
| lrn | |
| Contains classes for local response normalization layer. | |
| maximum_pooling1d | |
| Contains classes for maximum one-dimensional (1D) pooling layer. | |
| maximum_pooling2d | |
| Contains classes for maximum two-dimensional (2D) pooling layer. | |
| maximum_pooling3d | |
| Contains classes for maximum three-dimensional (3D) pooling layer. | |
| pooling1d | |
| Contains classes for the one-dimensional (1D) pooling layer. | |
| pooling2d | |
| Contains classes for the two-dimensional (2D) pooling layer. | |
| pooling3d | |
| Contains classes for the three-dimensional (3D) pooling layer. | |
| prelu | |
| Contains classes for the prelu layer. | |
| relu | |
| Contains classes for the relu layer. | |
| reshape | |
| Contains classes of the reshape layer. | |
| smoothrelu | |
| Contains classes for smooth relu layer. | |
| softmax | |
| Contains classes of the softmax layer. | |
| spatial_average_pooling2d | |
| Contains classes for spatial pyramid average two-dimensional (2D) pooling layer. | |
| spatial_maximum_pooling2d | |
| Contains classes for spatial pyramid maximum two-dimensional (2D) pooling layer. | |
| spatial_pooling2d | |
| Contains classes for the two-dimensional (2D) spatial layer. | |
| spatial_stochastic_pooling2d | |
| Contains classes for spatial pyramid stochastic two-dimensional (2D) pooling layer. | |
| split | |
| Contains classes for the split layer. | |
| stochastic_pooling2d | |
| Contains classes for stochastic two-dimensional (2D) pooling layer. | |
| tanh | |
| Contains classes for the hyperbolic tangent layer. | |
| transposed_conv2d | |
| Contains classes for neural network 2D transposed convolution layer. | |
Enumerations | |
| enum | LayerInputLayout |
| enum | LayerResultLayout |
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