Types used in Synet Framework. More...
Data Structures | |
struct | SimdConvolutionParameters |
Typedefs | |
typedef struct SimdConvolutionParameters | SimdConvolutionParameters |
Detailed Description
Types used in Synet Framework.
Typedef Documentation
◆ SimdConvolutionParameters
typedef struct SimdConvolutionParameters SimdConvolutionParameters |
Describes convolution (deconvolution) parameters. It is used in SimdSynetConvolution32fInit, SimdSynetConvolution8iInit, SimdSynetDeconvolution32fInit, SimdSynetMergedConvolution32fInit and SimdSynetMergedConvolution8iInit.
Enumeration Type Documentation
◆ SimdConvolutionActivationType
Describes type of activation function. It is used in SimdSynetConvolution32fInit, SimdSynetConvolution8iInit, SimdSynetDeconvolution32fInit, SimdSynetInnerProduct32fInit, SimdSynetMergedConvolution32fInit and SimdSynetMergedConvolution8iInit.
Enumerator | |
---|---|
SimdConvolutionActivationIdentity | Identity (activation function is absent). |
SimdConvolutionActivationRelu | ReLU activation function. dst[i] = Max(0, src[i]); |
SimdConvolutionActivationLeakyRelu | Leaky ReLU activation function. It has one parameter: slope (params[0]). dst[i] = src[i] > 0 ? src[i] : slope*src[i]; |
SimdConvolutionActivationRestrictRange | The activation function restricts range. It has two parameters: lower (params[0]) and upper (params[1]) bound. dst[i] = Min(Max(lower, src[i]), upper); |
SimdConvolutionActivationPrelu | Leaky PReLU activation function. It has m parameters: slopes[m] (m = dstC, n = dstH*dstW). dst[i*n + j] = src[i*n + j] > 0 ? src[i*n + j] : slopes[i]*src[i*n + j]; |
SimdConvolutionActivationElu | Leaky ELU activation function. It has one parameter: alpha (params[0]). dst[i] = src[i] >= 0 ? src[i] : alpha*(Exp(src[i]) - 1); |
SimdConvolutionActivationHswish | H-Swish (https://arxiv.org/pdf/1905.02244.pdf) activation function. It has two parameters: shift (params[0]) and scale (params[1]). dst[i] = Max(Min(src[i], shift) + shift, 0)*scale*src[i]; |
SimdConvolutionActivationMish | Mish (https://arxiv.org/abs/1908.08681) activation function. It has parameter: threshold (params[0]). dst[i] = src[i] > threshold ? src[i] : src[i] * tanh(log(exp(src[i]) + 1)); |
SimdConvolutionActivationHardSigmoid | HardSigmoid (https://pytorch.org/docs/stable/generated/torch.nn.Hardsigmoid.html) activation function. It has two parameters: scale (params[0]) and shift (params[1]). dst[i] = Max(0, Min(src[i] * scale + shift, 1)); |
SimdConvolutionActivationSwish | Swish (https://en.wikipedia.org/wiki/Swish_function) activation function. It has one parameter: slope (params[0]). dst[i] = src[i]/(1 + Exp(-slope*src[i])); |
◆ SimdSynetCompatibilityType
Describes Synet calculation compatibility flags. This type used in functions SimdSynetAdd8i, SimdSynetScaleLayerForward, SimdSynetConvert32fTo8u, SimdSynetConvert8uTo32f, SimdSynetInnerProduct8i, SimdSynetScale8iInit, SimdSynetConvolution32fInit, SimdSynetConvolution8iInit, SimdSynetMergedConvolution32fInit, SimdSynetMergedConvolution8iInit.
◆ SimdSynetEltwiseOperationType
Describes operation type used in function SimdSynetEltwiseLayerForward.
Enumerator | |
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SimdSynetEltwiseOperationProduct | Product. |
SimdSynetEltwiseOperationSum | Weighted sum. |
SimdSynetEltwiseOperationMax | Maximum. |
SimdSynetEltwiseOperationMin | Minimum. |
◆ SimdSynetUnaryOperation32fType
Describes operation type used in function SimdSynetUnaryOperation32fLayerForward.
◆ SimdTensorFormatType
enum SimdTensorFormatType |
Describes Synet Framework 4D-tensor format type.
Enumerator | |
---|---|
SimdTensorFormatUnknown | Unknown tensor format. |
SimdTensorFormatNchw | NCHW (N - batch, C - channels, H - height, W - width) 4D-tensor format of (input/output) image. |
SimdTensorFormatNhwc | NHWC (N - batch, H - height, W - width, C - channels) 4D-tensor format of (input/output) image. |
SimdTensorFormatNchw4c | NCHW4c (N - batch, C - (channels + 3) / 4, H - height, W - width, 4c - channels gropped by 4) special 5D-tensor format of (input/output) image optimized for SSE and NEON. |
SimdTensorFormatNchw8c | NCHW8c (N - batch, C - (channels + 7) / 8, H - height, W - width, 8c - channels gropped by 8) special 5D-tensor format of (input/output) image optimized for AVX and AVX2. |
SimdTensorFormatNchw16c | NCHW16c (N - batch, C - (channels + 15) / 16, H - height, W - width, 16c - channels gropped by 16) special 5D-tensor format of (input/output) image optimized for AVX-512. |
SimdTensorFormatNchwXc | Unspecified hardware optimized 5D-tensor format of (input/output) image. Specific format (SimdTensorFormatNchw4c, SimdTensorFormatNchw8c or SimdTensorFormatNchw16c) is determinated by function SimdSynetSpecifyTensorFormat. |
SimdTensorFormatOiyx | OIYX (O - output channels, I - input channels, Y - kernel height, X - kernel width) 4D-tensor format of 2D-convolution filter. |
SimdTensorFormatYxio | YXIO (Y - kernel height, X - kernel width, I - input channels, O - output channels) 4D-tensor format of 2D-convolution filter. |
SimdTensorFormatOyxi4o | OYXI4o (O - (output channels + 3)/4, Y - kernel height, X - kernel width, I - input channels, 4o - output channels gropped by 4) special 5D-tensor format of 2D-convolution filter optimized for SSE and NEON. |
SimdTensorFormatOyxi8o | OYXI8o (O - (output channels + 7)/8, Y - kernel height, X - kernel width, I - input channels, 8o - output channels gropped by 8) special 5D-tensor format of 2D-convolution filter optimized for AVX and AVX2. |
SimdTensorFormatOyxi16o | OYXI16o (O - (output channels + 15)/16, Y - kernel height, X - kernel width, I - input channels, 16o - output channels gropped by 16) special 5D-tensor format of 2D-convolution filter optimized for AVX-512. |
SimdTensorFormatOyxiXo | Unspecified hardware optimized 5D-tensor format of 2D-convolution filter. Specific format (SimdTensorFormatOyxi4o, SimdTensorFormatOyxi8o or SimdTensorFormatOyxi16o) is determinated by function SimdSynetSpecifyTensorFormat. |
◆ SimdTensorDataType
enum SimdTensorDataType |
Describes Synet Framework tensor data type.