diff options
Diffstat (limited to 'arm_compute/graph2/frontend/Layers.h')
| -rw-r--r-- | arm_compute/graph2/frontend/Layers.h | 66 |
1 files changed, 64 insertions, 2 deletions
diff --git a/arm_compute/graph2/frontend/Layers.h b/arm_compute/graph2/frontend/Layers.h index 40274a4769..7ea23e0684 100644 --- a/arm_compute/graph2/frontend/Layers.h +++ b/arm_compute/graph2/frontend/Layers.h @@ -45,6 +45,11 @@ namespace frontend class InputLayer final : public ILayer { public: + /** Construct an input layer. + * + * @param[in] desc Description of input tensor. + * @param[in] accessor Accessor to get input tensor data from. + */ InputLayer(TensorDescriptor desc, ITensorAccessorUPtr accessor) : _desc(desc), _accessor(std::move(accessor)) { @@ -65,6 +70,10 @@ private: class OutputLayer final : public ILayer { public: + /** Construct an output layer. + * + * @param[in] accessor Accessor to give output tensor data to. + */ OutputLayer(ITensorAccessorUPtr accessor) : _accessor(std::move(accessor)) { @@ -85,6 +94,10 @@ private: class ActivationLayer final : public ILayer { public: + /** Construct an activation layer. + * + * @param[in] act_info Activation information + */ ActivationLayer(ActivationLayerInfo act_info) : _act_info(act_info) { @@ -105,6 +118,14 @@ private: class BatchNormalizationLayer final : public ILayer { public: + /** Construct a batch normalization layer. + * + * @param[in] mean Accessor to get mean tensor data from. + * @param[in] var Accessor to get var tensor data from. + * @param[in] gamma (Optional) Accessor to get gamma tensor data from. Default: nullptr. + * @param[in] beta (Optional) Accessor to get beta tensor data from. Default: nullptr. + * @param[in] epsilon (Optional) Epsilon value. Default: 0.001. + */ BatchNormalizationLayer(ITensorAccessorUPtr mean, ITensorAccessorUPtr var, ITensorAccessorUPtr gamma = nullptr, @@ -137,6 +158,16 @@ private: class ConvolutionLayer final : public ILayer { public: + /** Construct a convolution layer. + * + * @param[in] conv_width Convolution width. + * @param[in] conv_height Convolution height. + * @param[in] ofm Output feature map. + * @param[in] weights Accessor to get kernel weights from. + * @param[in] bias Accessor to get kernel bias from. + * @param[in] conv_info Padding and stride information. + * @param[in] num_groups (Optional) Number of groups. Default: 1. + */ ConvolutionLayer(unsigned int conv_width, unsigned int conv_height, unsigned int ofm, @@ -179,6 +210,14 @@ private: class DepthwiseConvolutionLayer final : public ILayer { public: + /** Construct a depthwise convolution layer. + * + * @param[in] conv_width Convolution width. + * @param[in] conv_height Convolution height. + * @param[in] weights Accessor to get kernel weights from. + * @param[in] bias Accessor to get kernel bias from. + * @param[in] conv_info Padding and stride information. + */ DepthwiseConvolutionLayer(unsigned int conv_width, unsigned int conv_height, ITensorAccessorUPtr weights, @@ -214,6 +253,7 @@ private: class FlattenLayer final : public ILayer { public: + /** Construct a flatten layer. */ FlattenLayer() { } @@ -230,6 +270,12 @@ public: class FullyConnectedLayer final : public ILayer { public: + /** Construct a fully connected layer. + * + * @param[in] num_outputs Number of outputs. + * @param[in] weights Accessor to get weights from. + * @param[in] bias Accessor to get bias from. + */ FullyConnectedLayer(unsigned int num_outputs, ITensorAccessorUPtr weights, ITensorAccessorUPtr bias) @@ -255,6 +301,10 @@ private: class NormalizationLayer final : public ILayer { public: + /** Construct a normalization layer. + * + * @param[in] norm_info Normalization information. + */ NormalizationLayer(NormalizationLayerInfo norm_info) : _norm_info(norm_info) { @@ -275,6 +325,10 @@ private: class PoolingLayer final : public ILayer { public: + /** Construct a pooling layer. + * + * @param[in] pool_info Pooling information. + */ PoolingLayer(PoolingLayerInfo pool_info) : _pool_info(pool_info) { @@ -295,6 +349,10 @@ private: class ReshapeLayer final : public ILayer { public: + /** Construct a reshape layer. + * + * @param[in] shape Target shape. + */ ReshapeLayer(TensorShape shape) : _shape(shape) { @@ -315,6 +373,10 @@ private: class SoftmaxLayer final : public ILayer { public: + /** Construct a softmax layer. + * + * @param[in] beta (Optional) Beta value. Default 1.0. + */ SoftmaxLayer(float beta = 1.0f) : _beta(beta) { @@ -335,7 +397,7 @@ private: class BranchLayer final : public ILayer { public: - /** Default Constructor + /** Construct a branch layer * * @param[in] merge_method Branch merging method * @param[in] sub_stream1 First graph branch @@ -355,7 +417,7 @@ public: }, std::move(rest_sub_streams)...); } - /** Default Constructor + /** Construct a branch layer * * @param[in] sub_stream Sub-stream */ |