diff options
Diffstat (limited to 'docs/09_operators_list.dox')
-rw-r--r-- | docs/09_operators_list.dox | 719 |
1 files changed, 713 insertions, 6 deletions
diff --git a/docs/09_operators_list.dox b/docs/09_operators_list.dox index 244f292f82..fc41265738 100644 --- a/docs/09_operators_list.dox +++ b/docs/09_operators_list.dox @@ -145,6 +145,62 @@ where N = batches, C = channels, H = height, W = width <tr><td>F32<td>U32, S32 </table> <tr> + <td rowspan="1">ArithmeticAddition + <td rowspan="1" style="width:200px;"> Function to add 2 tensors. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_ADD + </ul> + <td>NEArithmeticAddition + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>QSYMM16<td>QSYMM16<td>S32 + <tr><td>U8<td>U8<td>U8 + <tr><td>U8<td>U8<td>S16 + <tr><td>U8<td>S16<td>S16 + <tr><td>S16<td>U8<td>S16 + <tr><td>S16<td>S16<td>S16 + <tr><td>S32<td>S32<td>S32 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td rowspan="1">ArithmeticSubtraction + <td rowspan="1" style="width:200px;"> Function to substract 2 tensors. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_SUB + </ul> + <td>NEArithmeticSubtraction + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>QSYMM16<td>QSYMM16<td>S32 + <tr><td>U8<td>U8<td>U8 + <tr><td>U8<td>U8<td>S16 + <tr><td>U8<td>S16<td>S16 + <tr><td>S16<td>U8<td>S16 + <tr><td>S16<td>S16<td>S16 + <tr><td>S32<td>S32<td>S32 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> <td rowspan="2">BatchNormalizationLayer <td rowspan="2" style="width:200px;"> Function to perform batch normalization. <td rowspan="2"> @@ -422,6 +478,28 @@ where N = batches, C = channels, H = height, W = width <tr><td>All<td>All </table> <tr> + <td rowspan="1">Comparison + <td rowspan="1" style="width:200px;"> Function to compare 2 tensors. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_EQUAL + <li>ANEURALNETWORKS_GREATER + <li>ANEURALNETWORKS_GREATER_EQUAL + <li>ANEURALNETWORKS_LESS + <li>ANEURALNETWORKS_LESS_EQUAL + <li>ANEURALNETWORKS_NOT_EQUAL + </ul> + <td>CLComparison + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>All<td>All<td>U8 + </table> +<tr> <td rowspan="2">ConcatenateLayer <td rowspan="2" style="width:200px;"> Function to concatenate tensors along a given axis. <td rowspan="2"> @@ -554,6 +632,23 @@ where N = batches, C = channels, H = height, W = width <tr><td>All<td>All </table> <tr> + <td rowspan="1">Crop + <td rowspan="1" style="width:200px;"> Performs a copy of input tensor to the output tensor. + <td rowspan="1"> + <ul> + <li>n/a + </ul> + <td>CLCrop + <td> + <ul> + <li>NHWC + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>All<td>F32 + </table> +<tr> <td rowspan="2">CropResize <td rowspan="2" style="width:200px;"> Function to perform cropping and resizing. <td rowspan="2"> @@ -622,6 +717,24 @@ where N = batches, C = channels, H = height, W = width <tr><td>QASYMM8_SIGNED<td>QSYMM8_PER_CHANNEL<td>S32<td>QASYMM8_SIGNED </table> <tr> + <td rowspan="1">DeconvolutionLayerUpsample + <td rowspan="1" style="width:200px;"> Function to execute deconvolution upsample on OpenCL. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_TRANSPOSE_CONV_2D + </ul> + <td>CLDeconvolutionLayerUpsample + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>All<td>All + </table> +<tr> <td rowspan="2">DepthConvertLayer <td rowspan="2" style="width:200px;"> Performs a down-scaling depth conversion. <td rowspan="2"> @@ -768,6 +881,25 @@ where N = batches, C = channels, H = height, W = width <tr><td>QSYMM16<td>F16, F32 </table> <tr> + <td rowspan="1">DetectionPostProcessLayer + <td rowspan="1" style="width:200px;"> Function to generate the detection output based on center size encoded boxes, class prediction and anchors by doing non maximum suppression (NMS). + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_DETECTION_POSTPROCESSING + </ul> + <td>NEDetectionPostProcessLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0 - src2<th>dst0 - dst3 + <tr><td>QASYMM8<td>F32 + <tr><td>QASYMM8_SIGNED<td>F32 + <tr><td>F32<td>F32 + </table> +<tr> <td rowspan="2">DirectConvolutionLayer <td rowspan="2" style="width:200px;"> Function to compute direct convolution. <td rowspan="2"> @@ -802,6 +934,364 @@ where N = batches, C = channels, H = height, W = width <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>S32<td>QASYMM8_SIGNED </table> <tr> + <td rowspan="1">DirectDeconvolutionLayer + <td rowspan="1" style="width:200px;"> Function to run the deconvolution layer. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_TRANSPOSE_CONV_2D + </ul> + <td>CLDirectDeconvolutionLayer + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>src2<th>dst + <tr><td>F16<td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32<td>F32 + <tr><td>QASYMM8<td>QASYMM8<td>S32<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>S32<td>QASYMM8_SIGNED + <tr><td>QASYMM8<td>QSYMM8_PER_CHANNEL<td>S32<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QSYMM8_PER_CHANNEL<td>S32<td>QASYMM8_SIGNED + </table> +<tr> + <td rowspan="13">ElementWiseOperations + <td rowspan="13" style="width:200px;"> Function to perform in Cpu: - Div - Max - Min - Pow - SquaredDiff - Comparisons (Equal, greater, greater_equal, less, less_equal, not_equal) Function to perform in CL: - Add - Sub - Div - Max - Min - Pow - SquaredDiff + <td rowspan="13"> + <ul> + <li>ANEURALNETWORKS_MAXIMUM + <li>ANEURALNETWORKS_MINIMUM + <li>ANEURALNETWORKS_POW + <li>ANEURALNETWORKS_DIV + <li>ANEURALNETWORKS_ADD + <li>ANEURALNETWORKS_SUB + <li>ANEURALNETWORKS_EQUAL + <li>ANEURALNETWORKS_GREATER + <li>ANEURALNETWORKS_GREATER_EQUAL + <li>ANEURALNETWORKS_LESS + <li>ANEURALNETWORKS_LESS_EQUAL + <li>ANEURALNETWORKS_NOT_EQUAL + </ul> + <td>NEElementwiseMax + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>S32<td>S32<td>S32 + <tr><td>S16<td>S16<td>S16 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>NEElementwiseMin + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>S32<td>S32<td>S32 + <tr><td>S16<td>S16<td>S16 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>NEElementwiseSquaredDiff + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>S32<td>S32<td>S32 + <tr><td>S16<td>S16<td>S16 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>NEElementwiseDivision + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>NEElementwisePower + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>NEElementwiseComparison + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>U8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>U8 + <tr><td>S32<td>S32<td>U8 + <tr><td>U8<td>U8<td>U8 + <tr><td>S16<td>S16<td>U8 + <tr><td>F16<td>F16<td>U8 + <tr><td>F32<td>F32<td>U8 + </table> +<tr> + <td>CLArithmeticAddition + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>U8<td>U8<td>U8 + <tr><td>U8<td>U8<td>S16 + <tr><td>U8<td>S16<td>S16 + <tr><td>S16<td>U8<td>S16 + <tr><td>S16<td>S16<td>S16 + <tr><td>S32<td>S32<td>S32 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>CLArithmeticSubtraction + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>U8<td>U8<td>U8 + <tr><td>U8<td>U8<td>S16 + <tr><td>U8<td>S16<td>S16 + <tr><td>S16<td>U8<td>S16 + <tr><td>S16<td>S16<td>S16 + <tr><td>S32<td>S32<td>S32 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>CLArithmeticDivision + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>CLElementwiseMax + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>U8<td>U8<td>U8 + <tr><td>S16<td>S16<td>S16 + <tr><td>S32<td>S32<td>S32 + <tr><td>U32<td>U32<td>U32 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>CLElementwiseMin + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>U8<td>U8<td>U8 + <tr><td>S16<td>S16<td>S16 + <tr><td>S32<td>S32<td>S32 + <tr><td>U32<td>U32<td>U32 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>CLElementwiseSquaredDiff + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>QSYMM16<td>QSYMM16<td>QASYMM16 + <tr><td>U8<td>U8<td>U8 + <tr><td>S16<td>S16<td>S16 + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td>CLElementwisePower + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32 + </table> +<tr> + <td rowspan="8">ElementwiseUnaryLayer + <td rowspan="8" style="width:200px;"> Function to perform: - Rsqrt - Exp - Neg - Log - Abs - Round - Sin + <td rowspan="8"> + <ul> + <li>ANEURALNETWORKS_ABS + <li>ANEURALNETWORKS_EXP + <li>ANEURALNETWORKS_LOG + <li>ANEURALNETWORKS_NEG + <li>ANEURALNETWORKS_RSQRT + <li>ANEURALNETWORKS_SIN + </ul> + <td>NEElementwiseUnaryLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + <tr><td>S32<td>S32 + </table> +<tr> + <td>CLRsqrtLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLExpLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLNegLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLSinLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLLogLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLAbsLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLRoundLayer + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> <td rowspan="2">FFT1D <td rowspan="2" style="width:200px;"> Fast Fourier Transform 1D. <td rowspan="2"> @@ -1009,7 +1499,7 @@ where N = batches, C = channels, H = height, W = width <ul> <li>ANEURALNETWORKS_FULLY_CONNECTED </ul> - <td>NEFullyConnectedLayerReshapeWeightsManaged + <td>NEFullyConnectedLayer <td> <ul> <li>NHWC @@ -1024,7 +1514,7 @@ where N = batches, C = channels, H = height, W = width <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>S32<td>QASYMM8_SIGNED </table> <tr> - <td>CLFullyConnectedLayerReshapeWeightsManaged + <td>CLFullyConnectedLayer <td> <ul> <li>NHWC @@ -1118,7 +1608,7 @@ where N = batches, C = channels, H = height, W = width <tr><td>BFLOAT16<td>BFLOAT16<td>BFLOAT16<td>BFLOAT16 </table> <tr> - <td>CLGEMMReshapeRHSMatrixKernelManaged + <td>CLGEMM <td> <ul> <li>All @@ -1130,13 +1620,34 @@ where N = batches, C = channels, H = height, W = width <tr><td>F16<td>F16<td>F16<td>F16 </table> <tr> + <td rowspan="1">GEMMConv2D + <td rowspan="1" style="width:200px;"> General Matrix Multiplication. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_CONV_2D + </ul> + <td>NEGEMMConv2d + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>src2<th>dst + <tr><td>QASYMM8<td>QASYMM8<td>S32<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>S32<td>QASYMM8_SIGNED + <tr><td>F16<td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32<td>F32 + <tr><td>BFLOAT16<td>BFLOAT16<td>BFLOAT16<td>BFLOAT16 + </table> +<tr> <td rowspan="2">GEMMConvolutionLayer <td rowspan="2" style="width:200px;"> General Matrix Multiplication. <td rowspan="2"> <ul> <li>ANEURALNETWORKS_CONV_2D </ul> - <td>NEConvolutionLayerReshapeWeights + <td>NEGEMMConvolutionLayer <td> <ul> <li>NHWC @@ -1154,7 +1665,7 @@ where N = batches, C = channels, H = height, W = width <tr><td>QASYMM8_SIGNED<td>QSYMM8_PER_CHANNEL<td>S32<td>QASYMM8_SIGNED </table> <tr> - <td>CLConvolutionLayerReshapeWeights + <td>CLGEMMConvolutionLayer <td> <ul> <li>NHWC @@ -1171,6 +1682,26 @@ where N = batches, C = channels, H = height, W = width <tr><td>QASYMM8_SIGNED<td>QSYMM8_PER_CHANNEL<td>S32<td>QASYMM8_SIGNED </table> <tr> + <td rowspan="1">GEMMDeconvolutionLayer + <td rowspan="1" style="width:200px;"> General Matrix Multiplication. + <td rowspan="1"> + <ul> + <li>ANEURALNETWORKS_TRANSPOSE_CONV_2D + </ul> + <td>CLGEMMDeconvolutionLayer + <td> + <ul> + <li>NHWC + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>src2<th>dst + <tr><td>F16<td>F16<td>F16<td>F16 + <tr><td>F32<td>F32<td>F32<td>F32 + <tr><td>QASYMM8<td>QASYMM8<td>S32<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED<td>S32<td>QASYMM8_SIGNED + </table> +<tr> <td rowspan="2">GEMMLowpMatrixMultiplyCore <td rowspan="2" style="width:200px;"> General Matrix Multiplication. <td rowspan="2"> @@ -1223,6 +1754,38 @@ where N = batches, C = channels, H = height, W = width <tr><td>QASYMM8_SIGNED<td>QSYMM8<td>S32<td>S32 </table> <tr> + <td rowspan="2">GEMMLowpOutputStage + <td rowspan="2" style="width:200px;"> General Matrix Multiplication. + <td rowspan="2"> + <ul> + <li>n/a + </ul> + <td>NEGEMMLowpOutputStage + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>S32<td>S32<td>QASYMM8 + <tr><td>S32<td>S32<td>QASYMM8_SIGNED + <tr><td>S32<td>S32<td>QSYMM16 + </table> +<tr> + <td>CLGEMMLowpOutputStage + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>S32<td>S32<td>QASYMM8 + <tr><td>S32<td>S32<td>QASYMM8_SIGNED + <tr><td>S32<td>S32<td>QSYMM16 + </table> +<tr> <td rowspan="2">GenerateProposalsLayer <td rowspan="2" style="width:200px;"> Function to generate proposals for a RPN (Region Proposal Network). <td rowspan="2"> @@ -1319,6 +1882,96 @@ where N = batches, C = channels, H = height, W = width <tr><td>F32<td>F32 </table> <tr> + <td rowspan="3">Logical + <td rowspan="3" style="width:200px;"> Function to perform: - Logical AND - Logical OR - Logical NOT + <td rowspan="3"> + <ul> + <li>n/a + </ul> + <td>NELogicalAnd + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>U8<td>U8<td>U8 + </table> +<tr> + <td>NELogicalOr + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>U8<td>U8<td>U8 + </table> +<tr> + <td>NELogicalNot + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>U8<td>U8 + </table> +<tr> + <td rowspan="1">LogicalAnd + <td rowspan="1" style="width:200px;"> Function to perform Logical AND. + <td rowspan="1"> + <ul> + <li>n/a + </ul> + <td>CLLogicalAnd + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>U8<td>U8<td>U8 + </table> +<tr> + <td rowspan="1">LogicalOr + <td rowspan="1" style="width:200px;"> Function to perform Logical OR. + <td rowspan="1"> + <ul> + <li>n/a + </ul> + <td>CLLogicalOr + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src0<th>src1<th>dst + <tr><td>U8<td>U8<td>U8 + </table> +<tr> + <td rowspan="1">LogicalNot + <td rowspan="1" style="width:200px;"> Function to perform Logical NOT. + <td rowspan="1"> + <ul> + <li>n/a + </ul> + <td>CLLogicalNot + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>U8<td>U8 + </table> +<tr> <td rowspan="2">LSTMLayer <td rowspan="2" style="width:200px;"> Function to perform a single time step in a Long Short-Term Memory (LSTM) layer. <td rowspan="2"> @@ -1660,7 +2313,7 @@ where N = batches, C = channels, H = height, W = width </table> <tr> <td rowspan="2">PriorBoxLayer - <td rowspan="2" style="width:200px;"> Function to . + <td rowspan="2" style="width:200px;"> Function to compute prior boxes and clip. <td rowspan="2"> <ul> <li>n/a @@ -2151,6 +2804,41 @@ where N = batches, C = channels, H = height, W = width <tr><td>All<td>All </table> <tr> + <td rowspan="2">SoftmaxLayer + <td rowspan="2" style="width:200px;"> Function to compute a SoftmaxLayer and a Log SoftmaxLayer. + <td rowspan="2"> + <ul> + <li>ANEURALNETWORKS_LOG_SOFTMAX + <li>ANEURALNETWORKS_SOFTMAX + </ul> + <td>NESoftmaxLayerGeneric + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> + <td>CLSoftmaxLayerGeneric + <td> + <ul> + <li>All + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>QASYMM8<td>QASYMM8 + <tr><td>QASYMM8_SIGNED<td>QASYMM8_SIGNED + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> +<tr> <td rowspan="2">SpaceToBatchLayer <td rowspan="2" style="width:200px;"> Function to divide a tensor spatially. <td rowspan="2"> @@ -2410,6 +3098,25 @@ where N = batches, C = channels, H = height, W = width <tr><td>F16<td>F16<td>F16<td>F16 <tr><td>F32<td>F32<td>F32<td>F32 </table> +<tr> + <td rowspan="1">WinogradInputTransform + <td rowspan="1" style="width:200px;"> Function to. + <td rowspan="1"> + <ul> + <li>n/a + </ul> + <td>CLWinogradInputTransform + <td> + <ul> + <li>NHWC + <li>NCHW + </ul> + <td> + <table> + <tr><th>src<th>dst + <tr><td>F16<td>F16 + <tr><td>F32<td>F32 + </table> </table> */ |