Revert "COMPMID-1329: Add support for GenerateProposals operator in CL"

This reverts commit cd96a26f67bfbb9b0efe6e0e2b229d0b46b4e3e6.

Change-Id: I1d46f37095c94968ad4f3b781269adaa03e2e410
Signed-off-by: giuros01 <giuseppe.rossini@arm.com>
Reviewed-on: https://review.mlplatform.org/706
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>

35 files changed, 34 insertions, 2018 deletions

diff --git a/arm_compute/core/CL/CLKernels.h b/arm_compute/core/CL/CLKernels.h
index cc4888c663..d8b9934313 100644
--- a/arm_compute/core/CL/CLKernels.h
+++ b/arm_compute/core/CL/CLKernels.h
@@ -89,7 +89,6 @@
 #include "arm_compute/core/CL/kernels/CLGaussian3x3Kernel.h"
 #include "arm_compute/core/CL/kernels/CLGaussian5x5Kernel.h"
 #include "arm_compute/core/CL/kernels/CLGaussianPyramidKernel.h"
-#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h"
 #include "arm_compute/core/CL/kernels/CLHOGDescriptorKernel.h"
 #include "arm_compute/core/CL/kernels/CLHOGDetectorKernel.h"
 #include "arm_compute/core/CL/kernels/CLHarrisCornersKernel.h"
diff --git a/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h b/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h
deleted file mode 100644
index 6c883348a5..0000000000
--- a/arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h
+++ /dev/null
@@ -1,76 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef __ARM_COMPUTE_CLGENERATEPROPOSALSLAYERKERNEL_H__
-#define __ARM_COMPUTE_CLGENERATEPROPOSALSLAYERKERNEL_H__
-
-#include "arm_compute/core/CL/ICLKernel.h"
-namespace arm_compute
-{
-class ICLTensor;
-
-/** Interface for Compute All Anchors kernel */
-class CLComputeAllAnchorsKernel : public ICLKernel
-{
-public:
-    /** Default constructor */
-    CLComputeAllAnchorsKernel();
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLComputeAllAnchorsKernel(const CLComputeAllAnchorsKernel &) = delete;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLComputeAllAnchorsKernel &operator=(const CLComputeAllAnchorsKernel &) = delete;
-    /** Allow instances of this class to be moved */
-    CLComputeAllAnchorsKernel(CLComputeAllAnchorsKernel &&) = default;
-    /** Allow instances of this class to be moved */
-    CLComputeAllAnchorsKernel &operator=(CLComputeAllAnchorsKernel &&) = default;
-    /** Default destructor */
-    ~CLComputeAllAnchorsKernel() = default;
-
-    /** Set the input and output tensors.
-     *
-     * @param[in]  anchors     Source tensor. Original set of anchors of size (4, A), where A is the number of anchors. Data types supported: F16/F32
-     * @param[out] all_anchors Destination tensor. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input
-     * @param[in]  info        Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo
-     *
-     */
-    void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info);
-
-    /** Static function to check if given info will lead to a valid configuration of @ref CLComputeAllAnchorsKernel
-     *
-     * @param[in] anchors     Source tensor info. Original set of anchors of size (4, A), where A is the number of anchors. Data types supported: F16/F32
-     * @param[in] all_anchors Destination tensor info. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input
-     * @param[in] info        Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo
-     *
-     * @return a Status
-     */
-    static Status validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info);
-
-    // Inherited methods overridden:
-    void run(const Window &window, cl::CommandQueue &queue) override;
-
-private:
-    const ICLTensor *_anchors;
-    ICLTensor       *_all_anchors;
-};
-} // arm_compute
-#endif // __ARM_COMPUTE_CLGENERATEPROSPOSALSLAYERKERNEL_H__
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 1ce44ee2e8..b0f792e92b 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -634,17 +634,13 @@ public:
      * @param[in] soft_nms_method          (Optional) Soft NMS method
      * @param[in] soft_nms_sigma           (Optional) Soft NMS sigma value
      * @param[in] soft_nms_min_score_thres (Optional) Soft NMS minimum score threshold
-     * @param[in] suppress_size            (Optional) Filter out boxes based on their size. Defaults to false
-     * @param[in] min_size                 (Optional) Smaller boxes than min_size will be filtered out. Defaults to 1
-     * @param[in] im_width                 (Optional) Boxes whose centers (on the x axis) is beyond im_width will be filtered. Defaults to 1
-     * @param[in] im_height                (Optional) Boxes whose centers (on the y axis) is beyond im_height will be filtered. Defaults to 1
      */
     BoxNMSLimitInfo(float score_thresh = 0.05f, float nms = 0.3f,
                     int detections = 100, bool soft_nms_enabled = false,
                     NMSType soft_nms_method = NMSType::LINEAR,
-                    float soft_nms_sigma = 0.5f, float soft_nms_min_score_thres = 0.001f, bool suppress_size = false, float min_size = 1.0f, float im_width = 1.0f, float im_height = 1.0f)
+                    float soft_nms_sigma = 0.5f, float soft_nms_min_score_thres = 0.001f)
         : _score_thresh(score_thresh), _nms(nms), _detections_per_im(detections), _soft_nms_enabled(soft_nms_enabled), _soft_nms_method(soft_nms_method), _soft_nms_sigma(soft_nms_sigma),
-          _soft_nms_min_score_thres(soft_nms_min_score_thres), _suppress_size(suppress_size), _min_size(min_size), _im_width(im_width), _im_height(im_height)
+          _soft_nms_min_score_thres(soft_nms_min_score_thres)
     {
     }
     /** Get the score threshold */
@@ -682,26 +678,6 @@ public:
     {
         return _soft_nms_min_score_thres;
     }
-    /** Get if NMS will suppress boxes based on their size/position */
-    bool suppress_size() const
-    {
-        return _suppress_size;
-    }
-    /** Get size suppression threshold */
-    float min_size() const
-    {
-        return _min_size;
-    }
-    /** Get image width (NMS may suppress boxes whose center sits beyond the image width) */
-    float im_width() const
-    {
-        return _im_width;
-    }
-    /** Get image height (NMS may suppress boxes whose center sits beyond the image height) */
-    float im_height() const
-    {
-        return _im_height;
-    }
 
 private:
     float   _score_thresh;
@@ -711,10 +687,6 @@ private:
     NMSType _soft_nms_method;
     float   _soft_nms_sigma;
     float   _soft_nms_min_score_thres;
-    bool    _suppress_size;
-    float   _min_size;
-    float   _im_width;
-    float   _im_height;
 };
 
 /** Padding and stride information class */
@@ -1245,137 +1217,6 @@ private:
     unsigned int _sampling_ratio;
 };
 
-/** Generate Proposals Information class */
-class GenerateProposalsInfo
-{
-public:
-    /** Constructor
-     *
-     * @param[in] im_width       Width of the original image
-     * @param[in] im_height      Height of the original image
-     * @param[in] im_scale       Scale applied to the original image
-     * @param[in] spatial_scale  (Optional)Scale applied to the feature map. Defaults to 1.0
-     * @param[in] pre_nms_topN   (Optional)Number of the best scores to be selected from the transformations. Defaults to 6000.
-     * @param[in] post_nms_topN  (Optional)Number of the best scores to be selected from the NMS operation. Defaults to 300.
-     * @param[in] nms_thres      (Optional)NMS overlap threshold. Defaults to 0.7.
-     * @param[in] min_size       (Optional)Size used to validate the anchors produced. Defaults to 16.
-     * @param[in] values_per_roi (Optional)Values used to represent a ROI(Region of interest). Defaults to 4.
-     */
-    GenerateProposalsInfo(float im_width, float im_height, float im_scale, float spatial_scale = 1.0, int pre_nms_topN = 6000, int post_nms_topN = 300, float nms_thres = 0.7, float min_size = 16.0,
-                          size_t values_per_roi = 4)
-        : _im_height(im_height), _im_width(im_width), _im_scale(im_scale), _spatial_scale(spatial_scale), _pre_nms_topN(pre_nms_topN), _post_nms_topN(post_nms_topN), _nms_thres(nms_thres),
-          _min_size(min_size), _values_per_roi(values_per_roi)
-    {
-    }
-
-    /* Get the original height */
-    float im_height() const
-    {
-        return _im_height;
-    }
-    /* Get the original width */
-    float im_width() const
-    {
-        return _im_width;
-    }
-    /* Get the image scale */
-    float im_scale() const
-    {
-        return _im_scale;
-    }
-    /* Get the value of how many best scores to select (before NMS) */
-    int pre_nms_topN() const
-    {
-        return _pre_nms_topN;
-    }
-    /* Get the value of how many best scores to select (after NMS) */
-    int post_nms_topN() const
-    {
-        return _post_nms_topN;
-    }
-    /* Get the NMS overlap threshold */
-    float nms_thres() const
-    {
-        return _nms_thres;
-    }
-    /* Get the minimal size */
-    float min_size() const
-    {
-        return _min_size;
-    }
-    /* Get the spatial scale to be applied to the feature maps */
-    float spatial_scale() const
-    {
-        return _spatial_scale;
-    }
-    /* Get the values used to represent a ROI(Region of interest)*/
-    size_t values_per_roi() const
-    {
-        return _values_per_roi;
-    }
-
-private:
-    float  _im_height;
-    float  _im_width;
-    float  _im_scale;
-    float  _spatial_scale;
-    int    _pre_nms_topN;
-    int    _post_nms_topN;
-    float  _nms_thres;
-    float  _min_size;
-    size_t _values_per_roi;
-};
-
-/** ComputeAnchors information class */
-class ComputeAnchorsInfo
-{
-public:
-    /** Constructor
-     *
-     * @param[in] feat_width     Feature map width
-     * @param[in] feat_height    Feature map height
-     * @param[in] spatial_scale  Feature map scale
-     * @param[in] values_per_roi (Optional)Values used to represent a ROI(Region Of Interest). Defaults to 4
-     */
-    ComputeAnchorsInfo(float feat_width, float feat_height, float spatial_scale, size_t values_per_roi = 4)
-        : _feat_height(feat_height),
-          _feat_width(feat_width),
-          _spatial_scale(spatial_scale),
-          _values_per_roi(values_per_roi)
-    {
-    }
-
-    /* Get the height of the feature map */
-    float feat_height() const
-    {
-        return _feat_height;
-    }
-
-    /* Get the width of the feature map */
-    float feat_width() const
-    {
-        return _feat_width;
-    }
-
-    /* Get the scale of the feature map */
-    float spatial_scale() const
-    {
-        return _spatial_scale;
-    }
-
-    /* Get the values used to represent a ROI(Region Of Interest)*/
-    size_t values_per_roi() const
-    {
-        return _values_per_roi;
-    }
-
-private:
-    float  _feat_height;
-    float  _feat_width;
-    float  _spatial_scale;
-    size_t _values_per_roi;
-};
-
 /** Bounding Box Transform information class */
 class BoundingBoxTransformInfo final
 {
diff --git a/arm_compute/graph/GraphBuilder.h b/arm_compute/graph/GraphBuilder.h
index b73f4f23ca..cf213e4e51 100644
--- a/arm_compute/graph/GraphBuilder.h
+++ b/arm_compute/graph/GraphBuilder.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -253,19 +253,6 @@ public:
                                             const FullyConnectedLayerInfo fc_info            = FullyConnectedLayerInfo(),
                                             const QuantizationInfo        weights_quant_info = QuantizationInfo(),
                                             const QuantizationInfo        out_quant_info     = QuantizationInfo());
-    /** Adds a generate proposals layer node to the graph
-     *
-     * @param[in] g       Graph to add the layer to
-     * @param[in] params  Common node parameters
-     * @param[in] scores  Input scores to the generate proposals layer node as a NodeID-Index pair
-     * @param[in] deltas  Input deltas to the generate proposals layer node as a NodeID-Index pair
-     * @param[in] anchors Input anchors to the generate proposals layer node as a NodeID-Index pair
-     * @param[in] info    Generate proposals operation information
-     *
-     * @return Node ID of the created node, EmptyNodeID in case of error
-     */
-    static NodeID add_generate_proposals_node(Graph &g, NodeParams params, NodeIdxPair scores, NodeIdxPair deltas,
-                                              NodeIdxPair anchors, GenerateProposalsInfo info);
     /** Adds a normalization layer node to the graph
      *
      * @param[in] g         Graph to add the node to
diff --git a/arm_compute/graph/TypePrinter.h b/arm_compute/graph/TypePrinter.h
index e33c984fd6..faa7f31911 100644
--- a/arm_compute/graph/TypePrinter.h
+++ b/arm_compute/graph/TypePrinter.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -98,9 +98,6 @@ inline ::std::ostream &operator<<(::std::ostream &os, const NodeType &node_type)
         case NodeType::FullyConnectedLayer:
             os << "FullyConnectedLayer";
             break;
-        case NodeType::GenerateProposalsLayer:
-            os << "GenerateProposalsLayer";
-            break;
         case NodeType::NormalizationLayer:
             os << "NormalizationLayer";
             break;
diff --git a/arm_compute/graph/Types.h b/arm_compute/graph/Types.h
index 60fe0a883e..ee136e2a1e 100644
--- a/arm_compute/graph/Types.h
+++ b/arm_compute/graph/Types.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -138,7 +138,6 @@ enum class NodeType
     EltwiseLayer,
     FlattenLayer,
     FullyConnectedLayer,
-    GenerateProposalsLayer,
     NormalizationLayer,
     NormalizePlanarYUVLayer,
     PadLayer,
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index 96adffee46..548afd27c5 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -688,55 +688,6 @@ std::unique_ptr<IFunction> create_fully_connected_layer(FullyConnectedLayerNode
     return std::move(func);
 }
 
-/** Create a backend generate proposals layer function
- *
- * @tparam GenerateProposalsLayerFunction Backend generate proposals function
- * @tparam TargetInfo                     Target-specific information
- *
- * @param[in] node Node to create the backend function for
- * @param[in] ctx  Graph context
- *
- * @return Backend generate proposals layer function
- */
-template <typename GenerateProposalsLayerFunction, typename TargetInfo>
-std::unique_ptr<IFunction> create_generate_proposals_layer(GenerateProposalsLayerNode &node, GraphContext &ctx)
-{
-    validate_node<TargetInfo>(node, 3 /* expected inputs */, 3 /* expected outputs */);
-
-    // Extract IO and info
-    typename TargetInfo::TensorType *scores              = get_backing_tensor<TargetInfo>(node.input(0));
-    typename TargetInfo::TensorType *deltas              = get_backing_tensor<TargetInfo>(node.input(1));
-    typename TargetInfo::TensorType *anchors             = get_backing_tensor<TargetInfo>(node.input(2));
-    typename TargetInfo::TensorType *proposals           = get_backing_tensor<TargetInfo>(node.output(0));
-    typename TargetInfo::TensorType *scores_out          = get_backing_tensor<TargetInfo>(node.output(1));
-    typename TargetInfo::TensorType *num_valid_proposals = get_backing_tensor<TargetInfo>(node.output(2));
-    const GenerateProposalsInfo      info                = node.info();
-
-    ARM_COMPUTE_ERROR_ON(scores == nullptr);
-    ARM_COMPUTE_ERROR_ON(deltas == nullptr);
-    ARM_COMPUTE_ERROR_ON(anchors == nullptr);
-    ARM_COMPUTE_ERROR_ON(proposals == nullptr);
-    ARM_COMPUTE_ERROR_ON(scores_out == nullptr);
-
-    // Create and configure function
-    auto func = support::cpp14::make_unique<GenerateProposalsLayerFunction>(get_memory_manager(ctx, TargetInfo::TargetType));
-    func->configure(scores, deltas, anchors, proposals, scores_out, num_valid_proposals, info);
-
-    // Log info
-    ARM_COMPUTE_LOG_GRAPH_INFO("Instantiated " << node.type()
-                               << " Target " << TargetInfo::TargetType
-                               << " Data Type: " << scores->info()->data_type()
-                               << " Scores shape: " << scores->info()->tensor_shape()
-                               << " Deltas shape: " << deltas->info()->tensor_shape()
-                               << " Anchors shape: " << anchors->info()->tensor_shape()
-                               << " Proposals shape: " << proposals->info()->tensor_shape()
-                               << " Num valid proposals shape: " << num_valid_proposals->info()->tensor_shape()
-                               << " Scores Out shape: " << scores_out->info()->tensor_shape()
-                               << std::endl);
-
-    return std::move(func);
-}
-
 /** Create a backend normalization layer function
  *
  * @tparam NormalizationLayerFunction Backend normalization function
diff --git a/arm_compute/graph/backends/ValidateHelpers.h b/arm_compute/graph/backends/ValidateHelpers.h
index f1e53613ab..1b06f31bed 100644
--- a/arm_compute/graph/backends/ValidateHelpers.h
+++ b/arm_compute/graph/backends/ValidateHelpers.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -228,33 +228,6 @@ Status validate_detection_output_layer(DetectionOutputLayerNode &node)
     return DetectionOutputLayer::validate(input0, input1, input2, output, detect_info);
 }
 
-/** Validates a Generate Proposals layer node
- *
- * @tparam GenerateProposalsLayer Generate Proposals layer type
- *
- * @param[in] node Node to validate
- *
- * @return Status
- */
-template <typename GenerateProposalsLayer>
-Status validate_generate_proposals_layer(GenerateProposalsLayerNode &node)
-{
-    ARM_COMPUTE_LOG_GRAPH_VERBOSE("Validating GenerateProposalsLayer node with ID : " << node.id() << " and Name: " << node.name() << std::endl);
-    ARM_COMPUTE_RETURN_ERROR_ON(node.num_inputs() != 3);
-    ARM_COMPUTE_RETURN_ERROR_ON(node.num_outputs() != 3);
-
-    // Extract IO and info
-    arm_compute::ITensorInfo   *scores              = detail::get_backing_tensor_info(node.input(0));
-    arm_compute::ITensorInfo   *deltas              = detail::get_backing_tensor_info(node.input(1));
-    arm_compute::ITensorInfo   *anchors             = detail::get_backing_tensor_info(node.input(2));
-    arm_compute::ITensorInfo   *proposals           = get_backing_tensor_info(node.output(0));
-    arm_compute::ITensorInfo   *scores_out          = get_backing_tensor_info(node.output(1));
-    arm_compute::ITensorInfo   *num_valid_proposals = get_backing_tensor_info(node.output(2));
-    const GenerateProposalsInfo info                = node.info();
-
-    return GenerateProposalsLayer::validate(scores, deltas, anchors, proposals, scores_out, num_valid_proposals, info);
-}
-
 /** Validates a NormalizePlanarYUV layer node
  *
  * @tparam NormalizePlanarYUVLayer layer type
diff --git a/arm_compute/graph/frontend/Layers.h b/arm_compute/graph/frontend/Layers.h
index 72353a2bbd..d10fa7f27a 100644
--- a/arm_compute/graph/frontend/Layers.h
+++ b/arm_compute/graph/frontend/Layers.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -608,44 +608,6 @@ private:
     const QuantizationInfo        _out_quant_info;
 };
 
-/** Generate Proposals Layer */
-class GenerateProposalsLayer final : public ILayer
-{
-public:
-    /** Construct a generate proposals layer.
-     *
-     * @param[in] ss_scores  Graph sub-stream for the scores.
-     * @param[in] ss_deltas  Graph sub-stream for the deltas.
-     * @param[in] ss_anchors Graph sub-stream for the anchors.
-     * @param[in] info       Generate Proposals operation information.
-     */
-    GenerateProposalsLayer(SubStream &&ss_scores, SubStream &&ss_deltas, SubStream &&ss_anchors, GenerateProposalsInfo info)
-        : _ss_scores(std::move(ss_scores)), _ss_deltas(std::move(ss_deltas)), _ss_anchors(std::move(ss_anchors)), _info(info)
-    {
-    }
-
-    /** Create layer and add to the given stream.
-     *
-     * @param[in] s Stream to add layer to.
-     *
-     * @return ID of the created node.
-     */
-    NodeID create_layer(IStream &s) override
-    {
-        NodeParams  common_params = { name(), s.hints().target_hint };
-        NodeIdxPair scores        = { _ss_scores.tail_node(), 0 };
-        NodeIdxPair deltas        = { _ss_deltas.tail_node(), 0 };
-        NodeIdxPair anchors       = { _ss_anchors.tail_node(), 0 };
-        return GraphBuilder::add_generate_proposals_node(s.graph(), common_params, scores, deltas, anchors, _info);
-    }
-
-private:
-    SubStream             _ss_scores;
-    SubStream             _ss_deltas;
-    SubStream             _ss_anchors;
-    GenerateProposalsInfo _info;
-};
-
 /** Normalization Layer */
 class NormalizationLayer final : public ILayer
 {
diff --git a/arm_compute/graph/nodes/GenerateProposalsLayerNode.h b/arm_compute/graph/nodes/GenerateProposalsLayerNode.h
deleted file mode 100644
index 09fbb3ee15..0000000000
--- a/arm_compute/graph/nodes/GenerateProposalsLayerNode.h
+++ /dev/null
@@ -1,60 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-
-#ifndef __ARM_COMPUTE_GENERATE_PROPOSALS_NODE_H__
-#define __ARM_COMPUTE_GENERATE_PROPOSALS_NODE_H__
-
-#include "arm_compute/graph/INode.h"
-
-namespace arm_compute
-{
-namespace graph
-{
-/** Generate Proposals Layer node */
-class GenerateProposalsLayerNode final : public INode
-{
-public:
-    /** Constructor
-     *
-     * @param[in] info Generate proposals operation information.
-     */
-    GenerateProposalsLayerNode(GenerateProposalsInfo &info);
-    /** GenerateProposalsInfo accessor
-     *
-     * @return GenerateProposalsInfo
-     */
-    const GenerateProposalsInfo &info() const;
-
-    // Inherited overridden methods:
-    NodeType         type() const override;
-    bool             forward_descriptors() override;
-    TensorDescriptor configure_output(size_t idx) const override;
-    void accept(INodeVisitor &v) override;
-
-private:
-    GenerateProposalsInfo _info;
-};
-} // namespace graph
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_GENERATE_PROPOSALS_NODE_H__ */
diff --git a/arm_compute/graph/nodes/Nodes.h b/arm_compute/graph/nodes/Nodes.h
index c85c4dc375..79ae5d4ae7 100644
--- a/arm_compute/graph/nodes/Nodes.h
+++ b/arm_compute/graph/nodes/Nodes.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -38,7 +38,6 @@
 #include "arm_compute/graph/nodes/EltwiseLayerNode.h"
 #include "arm_compute/graph/nodes/FlattenLayerNode.h"
 #include "arm_compute/graph/nodes/FullyConnectedLayerNode.h"
-#include "arm_compute/graph/nodes/GenerateProposalsLayerNode.h"
 #include "arm_compute/graph/nodes/InputNode.h"
 #include "arm_compute/graph/nodes/NormalizationLayerNode.h"
 #include "arm_compute/graph/nodes/NormalizePlanarYUVLayerNode.h"
diff --git a/arm_compute/graph/nodes/NodesFwd.h b/arm_compute/graph/nodes/NodesFwd.h
index 542c129ad6..6a0be1bf59 100644
--- a/arm_compute/graph/nodes/NodesFwd.h
+++ b/arm_compute/graph/nodes/NodesFwd.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -44,7 +44,6 @@ class DummyNode;
 class EltwiseLayerNode;
 class FlattenLayerNode;
 class FullyConnectedLayerNode;
-class GenerateProposalsLayerNode;
 class InputNode;
 class NormalizationLayerNode;
 class NormalizePlanarYUVLayerNode;
diff --git a/arm_compute/runtime/CL/CLFunctions.h b/arm_compute/runtime/CL/CLFunctions.h
index 686d266557..504443e806 100644
--- a/arm_compute/runtime/CL/CLFunctions.h
+++ b/arm_compute/runtime/CL/CLFunctions.h
@@ -44,7 +44,6 @@
 #include "arm_compute/runtime/CL/functions/CLChannelShuffleLayer.h"
 #include "arm_compute/runtime/CL/functions/CLColorConvert.h"
 #include "arm_compute/runtime/CL/functions/CLComparison.h"
-#include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h"
 #include "arm_compute/runtime/CL/functions/CLConcatenateLayer.h"
 #include "arm_compute/runtime/CL/functions/CLConvertFullyConnectedWeights.h"
 #include "arm_compute/runtime/CL/functions/CLConvolution.h"
@@ -80,7 +79,6 @@
 #include "arm_compute/runtime/CL/functions/CLGaussian3x3.h"
 #include "arm_compute/runtime/CL/functions/CLGaussian5x5.h"
 #include "arm_compute/runtime/CL/functions/CLGaussianPyramid.h"
-#include "arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h"
 #include "arm_compute/runtime/CL/functions/CLHOGDescriptor.h"
 #include "arm_compute/runtime/CL/functions/CLHOGDetector.h"
 #include "arm_compute/runtime/CL/functions/CLHOGGradient.h"
diff --git a/arm_compute/runtime/CL/functions/CLComputeAllAnchors.h b/arm_compute/runtime/CL/functions/CLComputeAllAnchors.h
deleted file mode 100644
index 6c6da791a1..0000000000
--- a/arm_compute/runtime/CL/functions/CLComputeAllAnchors.h
+++ /dev/null
@@ -1,62 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef __ARM_COMPUTE_CLCOMPUTEALLANCHORS_H__
-#define __ARM_COMPUTE_CLCOMPUTEALLANCHORS_H__
-
-#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h"
-#include "arm_compute/runtime/CL/ICLSimpleFunction.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** Basic function to run @ref CLComputeAllAnchorsKernel.
- *
- * This function calls the following OpenCL kernels:
- * -# @ref CLComputeAllAnchorsKernel
- */
-class CLComputeAllAnchors : public ICLSimpleFunction
-{
-public:
-    /** Set the input and output tensors.
-     *
-     * @param[in]  anchors     Source tensor. Original set of anchors of size (4, A) where A is the number of anchors. Data types supported: F16/F32
-     * @param[out] all_anchors Destination tensor. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input
-     * @param[in]  info        Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo
-     *
-     */
-    void configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info);
-
-    /** Static function to check if given info will lead to a valid configuration of @ref CLComputeAllAnchorsKernel
-     *
-     * @param[in] anchors     Source tensor info. Original set of anchors of size (4, A) where A is the number of anchors. Data types supported: F16/F32
-     * @param[in] all_anchors Destination tensor info. Destination anchors of size (4, H*W*A) where H and W are the height and width of the feature map and A is the number of anchors. Data types supported: Same as @p input
-     * @param[in] info        Contains Compute Anchors operation information described in @ref ComputeAnchorsInfo
-     *
-     * @return a Status
-     */
-    static Status validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info);
-};
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_CLCOMPUTEALLANCOHORS_H__ */
diff --git a/arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h b/arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h
deleted file mode 100644
index 02f5bd1ea8..0000000000
--- a/arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h
+++ /dev/null
@@ -1,148 +0,0 @@
-/*
- * Copyright (c) 2018-2019 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef __ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H__
-#define __ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H__
-#include "arm_compute/core/CL/kernels/CLBoundingBoxTransformKernel.h"
-#include "arm_compute/core/CL/kernels/CLCopyKernel.h"
-#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h"
-#include "arm_compute/core/CL/kernels/CLMemsetKernel.h"
-#include "arm_compute/core/CL/kernels/CLPermuteKernel.h"
-#include "arm_compute/core/CL/kernels/CLReshapeLayerKernel.h"
-#include "arm_compute/core/CL/kernels/CLStridedSliceKernel.h"
-#include "arm_compute/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.h"
-#include "arm_compute/core/Types.h"
-#include "arm_compute/runtime/CL/CLMemoryGroup.h"
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/CLTensor.h"
-#include "arm_compute/runtime/CPP/CPPScheduler.h"
-#include "arm_compute/runtime/IFunction.h"
-
-namespace arm_compute
-{
-class ICLTensor;
-
-/** Basic function to generate proposals for a RPN (Region Proposal Network)
- *
- * This function calls the following OpenCL kernels:
- * -# @ref CLComputeAllAnchors
- * -# @ref CLPermute x 2
- * -# @ref CLReshapeLayer x 2
- * -# @ref CLStridedSlice x 3
- * -# @ref CLBoundingBoxTransform
- * -# @ref CLCopyKernel
- * -# @ref CLMemsetKernel
- * And the following CPP kernels:
- * -# @ref CPPBoxWithNonMaximaSuppressionLimit
- */
-class CLGenerateProposalsLayer : public IFunction
-{
-public:
-    /** Default constructor
-     *
-     * @param[in] memory_manager (Optional) Memory manager.
-     */
-    CLGenerateProposalsLayer(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLGenerateProposalsLayer(const CLGenerateProposalsLayer &) = delete;
-    /** Default move constructor */
-    CLGenerateProposalsLayer(CLGenerateProposalsLayer &&) = default;
-    /** Prevent instances of this class from being copied (As this class contains pointers) */
-    CLGenerateProposalsLayer &operator=(const CLGenerateProposalsLayer &) = delete;
-    /** Default move assignment operator */
-    CLGenerateProposalsLayer &operator=(CLGenerateProposalsLayer &&) = default;
-
-    /** Set the input and output tensors.
-     *
-     * @param[in]  scores              Scores from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. Data types supported: F16/F32
-     * @param[in]  deltas              Bounding box deltas from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores
-     * @param[in]  anchors             Anchors tensor of size (4, A). Data types supported: Same as @p input
-     * @param[out] proposals           Box proposals output tensor of size (5, W*H*A). Data types supported: Same as @p input
-     * @param[out] scores_out          Box scores output tensor of size (W*H*A). Data types supported: Same as @p input
-     * @param[out] num_valid_proposals Scalar output tensor which says which of the first proposals are valid. Data types supported: U32
-     * @param[in]  info                Contains GenerateProposals operation information described in @ref GenerateProposalsInfo
-     *
-     * @note Only single image prediction is supported. Height and Width (and scale) of the image will be contained in the @ref GenerateProposalsInfo struct.
-     * @note Proposals contains all the proposals. Of those, only the first num_valid_proposals are valid.
-     */
-    void configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals,
-                   const GenerateProposalsInfo &info);
-
-    /** Static function to check if given info will lead to a valid configuration of @ref CLGenerateProposalsLayer
-     *
-     * @param[in] scores              Scores info from convolution layer of size (W, H, A), where H and W are the height and width of the feature map, and A is the number of anchors. Data types supported: F16/F32
-     * @param[in] deltas              Bounding box deltas info from convolution layer of size (W, H, 4*A). Data types supported: Same as @p scores
-     * @param[in] anchors             Anchors tensor info of size (4, A). Data types supported: Same as @p input
-     * @param[in] proposals           Box proposals info  output tensor of size (5, W*H*A). Data types supported: Data types supported: U32
-     * @param[in] scores_out          Box scores output tensor info of size (W*H*A). Data types supported: Same as @p input
-     * @param[in] num_valid_proposals Scalar output tensor info which says which of the first proposals are valid. Data types supported: Same as @p input
-     * @param[in] info                Contains GenerateProposals operation information described in @ref GenerateProposalsInfo
-     *
-     * @return a Status
-     */
-    static Status validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out,
-                           const ITensorInfo           *num_valid_proposals,
-                           const GenerateProposalsInfo &info);
-
-    // Inherited methods overridden:
-    void run() override;
-
-private:
-    // Memory group manager
-    CLMemoryGroup _memory_group;
-
-    // OpenCL kernels
-    CLPermuteKernel              _permute_deltas_kernel;
-    CLReshapeLayerKernel         _flatten_deltas_kernel;
-    CLPermuteKernel              _permute_scores_kernel;
-    CLReshapeLayerKernel         _flatten_scores_kernel;
-    CLComputeAllAnchorsKernel    _compute_anchors_kernel;
-    CLBoundingBoxTransformKernel _bounding_box_kernel;
-    CLMemsetKernel               _memset_kernel;
-    CLCopyKernel                 _padded_copy_kernel;
-
-    // CPP kernels
-    CPPBoxWithNonMaximaSuppressionLimitKernel _cpp_nms_kernel;
-
-    bool _is_nhwc;
-
-    // Temporary tensors
-    CLTensor _deltas_permuted;
-    CLTensor _deltas_flattened;
-    CLTensor _scores_permuted;
-    CLTensor _scores_flattened;
-    CLTensor _all_anchors;
-    CLTensor _all_proposals;
-    CLTensor _keeps_nms_unused;
-    CLTensor _classes_nms_unused;
-    CLTensor _proposals_4_roi_values;
-
-    // Output tensor pointers
-    ICLTensor *_num_valid_proposals;
-    ICLTensor *_scores_out;
-
-    /** Internal function to run the CPP BoxWithNMS kernel */
-    void run_cpp_nms_kernel();
-};
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_CLGENERATEPROPOSALSLAYER_H__ */
diff --git a/docs/00_introduction.dox b/docs/00_introduction.dox
index f722836124..75a8bf9ab4 100644
--- a/docs/00_introduction.dox
+++ b/docs/00_introduction.dox
@@ -290,7 +290,6 @@ v19.02 Public major release
  - New CPP kernels / functions:
     - @ref CPPDetectionOutputLayer
     - @ref CPPTopKV / @ref CPPTopKVKernel
-    - @ref CPPNonMaximumSuppression
  - Added new examples:
     - graph_ssd_mobilenet.cpp
     - graph_mobilenet_v2.cpp
@@ -314,7 +313,6 @@ v19.02 Public major release
     - @ref NEL2NormalizeLayer for FP32/FP16
     - @ref NENormalizationLayer IN_MAP_2D for FP32/FP16
     - @ref CLROIAlignLayer
-    - @ref CLGenerateProposalsLayer
  - Added QASYMM8 support to the following kernels:
     - @ref NEArithmeticAdditionKernel
     - @ref NEScale
@@ -335,8 +333,6 @@ v18.11 Public major release
  - New OpenCL kernels / functions:
     - @ref CLBatchToSpaceLayer / @ref CLBatchToSpaceLayerKernel
     - @ref CLBoundingBoxTransform / @ref CLBoundingBoxTransformKernel
-    - @ref CLComputeAllAnchorsKernel
-    - @ref CLGenerateProposalsLayer
     - @ref CLNormalizePlanarYUVLayer / @ref CLNormalizePlanarYUVLayerKernel
     - @ref CLReorgLayer / @ref CLReorgLayerKernel
     - @ref CLSpaceToBatchLayer / @ref CLSpaceToBatchLayerKernel
diff --git a/docs/05_functions_list.dox b/docs/05_functions_list.dox
index 6b94d8c924..3493e8aeba 100644
--- a/docs/05_functions_list.dox
+++ b/docs/05_functions_list.dox
@@ -195,7 +195,6 @@ namespace arm_compute
     - @ref CLGEMM
     - @ref CLGEMMConvolutionLayer
     - @ref CLGEMMLowpMatrixMultiplyCore
-    - @ref CLGenerateProposalsLayer
     - @ref CLHarrisCorners
     - @ref CLHistogram
     - @ref CLHOGDescriptor
@@ -251,7 +250,6 @@ namespace arm_compute
         - @ref CLColorConvert
         - @ref CLComparison
         - @ref CLComparisonStatic
-        - @ref CLComputeAllAnchors
         - @ref CLConvertFullyConnectedWeights
         - @ref CLConvolution3x3
         - @ref CLConvolutionRectangle
@@ -339,7 +337,6 @@ namespace arm_compute
 @section S5_4 CPP functions
 
  - @ref IFunction
-    - @ref CPPNonMaximumSuppression
     - @ref CPPDetectionOutputLayer
     - @ref ICPPSimpleFunction
         - @ref CPPBoxWithNonMaximaSuppressionLimit
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 2176c59f94..ce846d1dc5 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -306,7 +306,6 @@ const std::map<std::string, std::string> CLKernelLibrary::_kernel_program_map =
     { "gemmlowp_output_stage_quantize_down", "gemmlowp.cl" },
     { "gemmlowp_output_stage_quantize_down_fixedpoint", "gemmlowp.cl" },
     { "gemmlowp_output_stage_quantize_down_float", "gemmlowp.cl" },
-    { "generate_proposals_compute_all_anchors", "generate_proposals.cl" },
     { "harris_score_3x3", "harris_corners.cl" },
     { "harris_score_5x5", "harris_corners.cl" },
     { "harris_score_7x7", "harris_corners.cl" },
@@ -706,10 +705,6 @@ const std::map<std::string, std::string> CLKernelLibrary::_program_source_map =
 #include "./cl_kernels/gemv.clembed"
     },
     {
-        "generate_proposals.cl",
-#include "./cl_kernels/generate_proposals.clembed"
-    },
-    {
         "harris_corners.cl",
 #include "./cl_kernels/harris_corners.clembed"
     },
diff --git a/src/core/CL/cl_kernels/bounding_box_transform.cl b/src/core/CL/cl_kernels/bounding_box_transform.cl
index 097235549b..77db5d9311 100644
--- a/src/core/CL/cl_kernels/bounding_box_transform.cl
+++ b/src/core/CL/cl_kernels/bounding_box_transform.cl
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -28,11 +28,11 @@
 /** Perform a padded copy of input tensor to the output tensor. Padding values are defined at compile time
  *
  * @attention The following variables must be passed at compile time:
- * -# -DDATA_TYPE= Tensor data type. Supported data types: F16/F32
+ * -# -DDATA_TYPE = Tensor data type. Supported data types: F16/F32
  * -# -DWEIGHT{X,Y,W,H}= Weights [wx, wy, ww, wh] for the deltas
  * -# -DIMG_WIDTH= Original image width
  * -# -DIMG_HEIGHT= Original image height
- * -# -DBOX_FIELDS= Number of fields that are used to represent a box in boxes
+ * -# -DBOX_FIELDS=Number of fields that are used to represent a box in boxes
  *
  * @param[in]  boxes_ptr                                Pointer to the boxes tensor. Supported data types: F16/F32
  * @param[in]  boxes_stride_x                           Stride of the boxes tensor in X dimension (in bytes)
diff --git a/src/core/CL/cl_kernels/generate_proposals.cl b/src/core/CL/cl_kernels/generate_proposals.cl
deleted file mode 100644
index bc6f4b5e17..0000000000
--- a/src/core/CL/cl_kernels/generate_proposals.cl
+++ /dev/null
@@ -1,88 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "helpers.h"
-
-/** Generate all the region of interests based on the image size and the anchors passed in. For each element (x,y) of the
- * grid, it will generate NUM_ANCHORS rois, given by shifting the grid position to match the anchor.
- *
- * @attention The following variables must be passed at compile time:
- * -# -DDATA_TYPE= Tensor data type. Supported data types: F16/F32
- * -# -DHEIGHT= Height of the feature map on which this kernel is applied
- * -# -DWIDTH= Width of the feature map on which this kernel is applied
- * -# -DNUM_ANCHORS= Number of anchors to be used to generate the rois per each pixel
- * -# -DSTRIDE= Stride to be applied at each different pixel position (i.e., x_range = (1:WIDTH)*STRIDE and y_range = (1:HEIGHT)*STRIDE
- * -# -DNUM_ROI_FIELDS= Number of fields used to represent a roi
- *
- * @param[in]  anchors_ptr                           Pointer to the anchors tensor. Supported data types: F16/F32
- * @param[in]  anchors_stride_x                      Stride of the anchors tensor in X dimension (in bytes)
- * @param[in]  anchors_step_x                        anchors_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[in]  anchors_stride_y                      Stride of the anchors tensor in Y dimension (in bytes)
- * @param[in]  anchors_step_y                        anchors_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[in]  anchors_stride_z                      Stride of the source tensor in Z dimension (in bytes)
- * @param[in]  anchors_step_z                        anchors_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[in]  anchors_offset_first_element_in_bytes The offset of the first element in the boxes tensor
- * @param[out] rois_ptr                              Pointer to the rois. Supported data types: same as @p in_ptr
- * @param[out] rois_stride_x                         Stride of the rois in X dimension (in bytes)
- * @param[out] rois_step_x                           pred_boxes_stride_x * number of elements along X processed per workitem(in bytes)
- * @param[out] rois_stride_y                         Stride of the rois in Y dimension (in bytes)
- * @param[out] rois_step_y                           pred_boxes_stride_y * number of elements along Y processed per workitem(in bytes)
- * @param[out] rois_stride_z                         Stride of the rois in Z dimension (in bytes)
- * @param[out] rois_step_z                           pred_boxes_stride_z * number of elements along Z processed per workitem(in bytes)
- * @param[out] rois_offset_first_element_in_bytes    The offset of the first element in the rois
- */
-#if defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(NUM_ANCHORS) && defined(STRIDE) && defined(NUM_ROI_FIELDS)
-__kernel void generate_proposals_compute_all_anchors(
-    VECTOR_DECLARATION(anchors),
-    VECTOR_DECLARATION(rois))
-{
-    Vector anchors = CONVERT_TO_VECTOR_STRUCT_NO_STEP(anchors);
-    Vector rois    = CONVERT_TO_VECTOR_STRUCT(rois);
-
-    const size_t idx = get_global_id(0);
-    // Find the index of the anchor
-    const size_t anchor_idx = idx % NUM_ANCHORS;
-
-    // Find which shift is this thread using
-    const size_t shift_idx = idx / NUM_ANCHORS;
-
-    // Compute the shift on the X and Y direction (the shift depends exclusively by the index thread id)
-    const DATA_TYPE
-    shift_x = (DATA_TYPE)(shift_idx % WIDTH) * STRIDE;
-    const DATA_TYPE
-    shift_y = (DATA_TYPE)(shift_idx / WIDTH) * STRIDE;
-
-    const VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS)
-    shift = (VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS))(shift_x, shift_y, shift_x, shift_y);
-
-    // Read the given anchor
-    const VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS)
-    anchor = vload4(0, (__global DATA_TYPE *)vector_offset(&anchors, anchor_idx * NUM_ROI_FIELDS));
-
-    // Apply the shift to the anchor
-    const VEC_DATA_TYPE(DATA_TYPE, NUM_ROI_FIELDS)
-    shifted_anchor = anchor + shift;
-
-    vstore4(shifted_anchor, 0, (__global DATA_TYPE *)rois.ptr);
-}
-#endif //defined(DATA_TYPE) && defined(WIDTH) && defined(HEIGHT) && defined(NUM_ANCHORS) && defined(STRIDE) && defined(NUM_ROI_FIELDS)
diff --git a/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp b/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp
deleted file mode 100644
index 5d100a4c1e..0000000000
--- a/src/core/CL/kernels/CLGenerateProposalsLayerKernel.cpp
+++ /dev/null
@@ -1,128 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "arm_compute/core/CL/kernels/CLGenerateProposalsLayerKernel.h"
-
-#include "arm_compute/core/AccessWindowStatic.h"
-#include "arm_compute/core/CL/CLHelpers.h"
-#include "arm_compute/core/CL/CLKernelLibrary.h"
-#include "arm_compute/core/CL/CLValidate.h"
-#include "arm_compute/core/CL/ICLArray.h"
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "arm_compute/core/CL/OpenCL.h"
-#include "arm_compute/core/Helpers.h"
-#include "arm_compute/core/TensorInfo.h"
-#include "arm_compute/core/Utils.h"
-#include "arm_compute/core/Window.h"
-
-namespace arm_compute
-{
-namespace
-{
-Status validate_arguments(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info)
-{
-    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(anchors, all_anchors);
-    ARM_COMPUTE_RETURN_ERROR_ON(anchors->dimension(0) != info.values_per_roi());
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_NOT_IN(anchors, DataType::F16, DataType::F32);
-    ARM_COMPUTE_RETURN_ERROR_ON(anchors->num_dimensions() > 2);
-    if(all_anchors->total_size() > 0)
-    {
-        size_t feature_height = info.feat_height();
-        size_t feature_width  = info.feat_width();
-        size_t num_anchors    = anchors->dimension(1);
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(all_anchors, anchors);
-        ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->num_dimensions() > 2);
-        ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(0) != info.values_per_roi());
-        ARM_COMPUTE_RETURN_ERROR_ON(all_anchors->dimension(1) != feature_height * feature_width * num_anchors);
-    }
-    return Status{};
-}
-} // namespace
-
-CLComputeAllAnchorsKernel::CLComputeAllAnchorsKernel()
-    : _anchors(nullptr), _all_anchors(nullptr)
-{
-}
-
-void CLComputeAllAnchorsKernel::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info)
-{
-    ARM_COMPUTE_ERROR_ON_NULLPTR(anchors, all_anchors);
-    ARM_COMPUTE_ERROR_THROW_ON(validate_arguments(anchors->info(), all_anchors->info(), info));
-
-    // Metadata
-    const size_t   num_anchors = anchors->info()->dimension(1);
-    const DataType data_type   = anchors->info()->data_type();
-    const float    width       = info.feat_width();
-    const float    height      = info.feat_height();
-
-    // Initialize the output if empty
-    const TensorShape output_shape(info.values_per_roi(), width * height * num_anchors);
-    auto_init_if_empty(*all_anchors->info(), output_shape, 1, data_type);
-
-    // Set instance variables
-    _anchors     = anchors;
-    _all_anchors = all_anchors;
-
-    // Set build options
-    CLBuildOptions build_opts;
-    build_opts.add_option("-DDATA_TYPE=" + get_cl_type_from_data_type(data_type));
-    build_opts.add_option("-DWIDTH=" + float_to_string_with_full_precision(width));
-    build_opts.add_option("-DHEIGHT=" + float_to_string_with_full_precision(height));
-    build_opts.add_option("-DSTRIDE=" + float_to_string_with_full_precision(1.f / info.spatial_scale()));
-    build_opts.add_option("-DNUM_ANCHORS=" + support::cpp11::to_string(num_anchors));
-    build_opts.add_option("-DNUM_ROI_FIELDS=" + support::cpp11::to_string(info.values_per_roi()));
-
-    // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("generate_proposals_compute_all_anchors", build_opts.options()));
-
-    // The tensor all_anchors can be interpreted as an array of structs (each structs has values_per_roi fields).
-    // This means we don't need to pad on the X dimension, as we know in advance how many fields
-    // compose the struct.
-    Window win = calculate_max_window(*all_anchors->info(), Steps(info.values_per_roi()));
-    ICLKernel::configure_internal(win);
-}
-
-Status CLComputeAllAnchorsKernel::validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info)
-{
-    ARM_COMPUTE_RETURN_ON_ERROR(validate_arguments(anchors, all_anchors, info));
-    return Status{};
-}
-
-void CLComputeAllAnchorsKernel::run(const Window &window, cl::CommandQueue &queue)
-{
-    ARM_COMPUTE_ERROR_ON_UNCONFIGURED_KERNEL(this);
-    ARM_COMPUTE_ERROR_ON_INVALID_SUBWINDOW(IKernel::window(), window);
-
-    // Collapse everything on the first dimension
-    Window collapsed = window.collapse(ICLKernel::window(), Window::DimX);
-
-    // Set arguments
-    unsigned int idx = 0;
-    add_1D_tensor_argument(idx, _anchors, collapsed);
-    add_1D_tensor_argument(idx, _all_anchors, collapsed);
-
-    // Note that we don't need to loop over the slices, as we are launching exactly
-    // as many threads as all the anchors generated
-    enqueue(queue, *this, collapsed);
-}
-} // namespace arm_compute
diff --git a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp
index 06a0551e46..5e4b80aa5a 100644
--- a/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp
+++ b/src/core/CPP/kernels/CPPBoxWithNonMaximaSuppressionLimitKernel.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -54,7 +54,7 @@ std::vector<int> SoftNMS(const ITensor *proposals, std::vector<std::vector<T>> &
         areas[i] = (x2[i] - x1[i] + 1.0) * (y2[i] - y1[i] + 1.0);
     }
 
-    // Note: Soft NMS scores have already been initialized with input scores
+    // Note: Soft NMS scores have already been initialize with input scores
 
     while(!inds.empty())
     {
@@ -150,21 +150,17 @@ std::vector<int> NonMaximaSuppression(const ITensor *proposals, std::vector<int>
 
         for(unsigned int j = 0; j < sorted_indices_temp.size(); ++j)
         {
-            const float xx1 = std::max(x1[sorted_indices_temp.at(j)], x1[i]);
-            const float yy1 = std::max(y1[sorted_indices_temp.at(j)], y1[i]);
-            const float xx2 = std::min(x2[sorted_indices_temp.at(j)], x2[i]);
-            const float yy2 = std::min(y2[sorted_indices_temp.at(j)], y2[i]);
-
-            const float w     = std::max((xx2 - xx1 + 1.f), 0.f);
-            const float h     = std::max((yy2 - yy1 + 1.f), 0.f);
-            const float inter = w * h;
-            const float ovr   = inter / (areas[i] + areas[sorted_indices_temp.at(j)] - inter);
-            const float ctr_x = xx1 + (w / 2);
-            const float ctr_y = yy1 + (h / 2);
-
-            // If suppress_size is specified, filter the boxes based on their size and position
-            const bool keep_size = !info.suppress_size() || (w >= info.min_size() && h >= info.min_size() && ctr_x < info.im_width() && ctr_y < info.im_height());
-            if(ovr <= info.nms() && keep_size)
+            const auto xx1 = std::max(x1[sorted_indices_temp.at(j)], x1[i]);
+            const auto yy1 = std::max(y1[sorted_indices_temp.at(j)], y1[i]);
+            const auto xx2 = std::min(x2[sorted_indices_temp.at(j)], x2[i]);
+            const auto yy2 = std::min(y2[sorted_indices_temp.at(j)], y2[i]);
+
+            const auto w     = std::max((xx2 - xx1 + 1.f), 0.f);
+            const auto h     = std::max((yy2 - yy1 + 1.f), 0.f);
+            const auto inter = w * h;
+            const auto ovr   = inter / (areas[i] + areas[sorted_indices_temp.at(j)] - inter);
+
+            if(ovr <= info.nms())
             {
                 new_indices.push_back(j);
             }
@@ -218,9 +214,8 @@ void CPPBoxWithNonMaximaSuppressionLimitKernel::run_nmslimit()
     for(int b = 0; b < batch_size; ++b)
     {
         const int num_boxes = _batch_splits_in == nullptr ? 1 : static_cast<int>(*reinterpret_cast<T *>(_batch_splits_in->ptr_to_element(Coordinates(b))));
-        // Skip first class if there is more than 1 except if the number of classes is 1.
-        const int j_start = (num_classes == 1 ? 0 : 1);
-        for(int j = j_start; j < num_classes; ++j)
+        // Skip first class
+        for(int j = 1; j < num_classes; ++j)
         {
             std::vector<T>   cur_scores(scores_count);
             std::vector<int> inds;
@@ -295,7 +290,7 @@ void CPPBoxWithNonMaximaSuppressionLimitKernel::run_nmslimit()
 
         // Write results
         int cur_out_idx = 0;
-        for(int j = j_start; j < num_classes; ++j)
+        for(int j = 1; j < num_classes; ++j)
         {
             auto     &cur_keep        = keeps[j];
             auto      cur_out_scores  = reinterpret_cast<T *>(_scores_out->ptr_to_element(Coordinates(cur_start_idx + cur_out_idx)));
diff --git a/src/graph/GraphBuilder.cpp b/src/graph/GraphBuilder.cpp
index d09002d69b..cac1a37099 100644
--- a/src/graph/GraphBuilder.cpp
+++ b/src/graph/GraphBuilder.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -448,22 +448,6 @@ NodeID GraphBuilder::add_fully_connected_layer(Graph &g, NodeParams params, Node
     return fc_nid;
 }
 
-NodeID GraphBuilder::add_generate_proposals_node(Graph &g, NodeParams params, NodeIdxPair scores, NodeIdxPair deltas, NodeIdxPair anchors, GenerateProposalsInfo info)
-{
-    CHECK_NODEIDX_PAIR(scores, g);
-    CHECK_NODEIDX_PAIR(deltas, g);
-    CHECK_NODEIDX_PAIR(anchors, g);
-
-    NodeID nid = g.add_node<GenerateProposalsLayerNode>(info);
-
-    g.add_connection(scores.node_id, scores.index, nid, 0);
-    g.add_connection(deltas.node_id, deltas.index, nid, 1);
-    g.add_connection(anchors.node_id, anchors.index, nid, 2);
-
-    set_node_params(g, nid, params);
-    return nid;
-}
-
 NodeID GraphBuilder::add_normalization_node(Graph &g, NodeParams params, NodeIdxPair input, NormalizationLayerInfo norm_info)
 {
     return create_simple_single_input_output_node<NormalizationLayerNode>(g, params, input, norm_info);
diff --git a/src/graph/backends/CL/CLFunctionsFactory.cpp b/src/graph/backends/CL/CLFunctionsFactory.cpp
index 5b329c04be..88d8e3c6c5 100644
--- a/src/graph/backends/CL/CLFunctionsFactory.cpp
+++ b/src/graph/backends/CL/CLFunctionsFactory.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -192,8 +192,6 @@ std::unique_ptr<IFunction> CLFunctionFactory::create(INode *node, GraphContext &
             return detail::create_flatten_layer<CLFlattenLayer, CLTargetInfo>(*polymorphic_downcast<FlattenLayerNode *>(node));
         case NodeType::FullyConnectedLayer:
             return detail::create_fully_connected_layer<CLFullyConnectedLayer, CLTargetInfo>(*polymorphic_downcast<FullyConnectedLayerNode *>(node), ctx);
-        case NodeType::GenerateProposalsLayer:
-            return detail::create_generate_proposals_layer<CLGenerateProposalsLayer, CLTargetInfo>(*polymorphic_downcast<GenerateProposalsLayerNode *>(node), ctx);
         case NodeType::NormalizationLayer:
             return detail::create_normalization_layer<CLNormalizationLayer, CLTargetInfo>(*polymorphic_downcast<NormalizationLayerNode *>(node), ctx);
         case NodeType::NormalizePlanarYUVLayer:
diff --git a/src/graph/backends/CL/CLNodeValidator.cpp b/src/graph/backends/CL/CLNodeValidator.cpp
index 85ac1f59c6..ca327c9771 100644
--- a/src/graph/backends/CL/CLNodeValidator.cpp
+++ b/src/graph/backends/CL/CLNodeValidator.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -62,8 +62,6 @@ Status CLNodeValidator::validate(INode *node)
                    CLDepthwiseConvolutionLayer3x3>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
         case NodeType::DetectionOutputLayer:
             return detail::validate_detection_output_layer<CPPDetectionOutputLayer>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
-        case NodeType::GenerateProposalsLayer:
-            return detail::validate_generate_proposals_layer<CLGenerateProposalsLayer>(*polymorphic_downcast<GenerateProposalsLayerNode *>(node));
         case NodeType::NormalizePlanarYUVLayer:
             return detail::validate_normalize_planar_yuv_layer<CLNormalizePlanarYUVLayer>(*polymorphic_downcast<NormalizePlanarYUVLayerNode *>(node));
         case NodeType::PadLayer:
diff --git a/src/graph/backends/GLES/GCNodeValidator.cpp b/src/graph/backends/GLES/GCNodeValidator.cpp
index 95bb44f5cc..aaa031dbb9 100644
--- a/src/graph/backends/GLES/GCNodeValidator.cpp
+++ b/src/graph/backends/GLES/GCNodeValidator.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -115,8 +115,6 @@ Status GCNodeValidator::validate(INode *node)
             return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : DetectionOutputLayer");
         case NodeType::FlattenLayer:
             return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : FlattenLayer");
-        case NodeType::GenerateProposalsLayer:
-            return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : GenerateProposalsLayer");
         case NodeType::NormalizePlanarYUVLayer:
             return detail::validate_normalize_planar_yuv_layer<GCNormalizePlanarYUVLayer>(*polymorphic_downcast<NormalizePlanarYUVLayerNode *>(node));
         case NodeType::PadLayer:
diff --git a/src/graph/backends/NEON/NENodeValidator.cpp b/src/graph/backends/NEON/NENodeValidator.cpp
index db6af5eab7..96236b66c3 100644
--- a/src/graph/backends/NEON/NENodeValidator.cpp
+++ b/src/graph/backends/NEON/NENodeValidator.cpp
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -62,8 +62,6 @@ Status NENodeValidator::validate(INode *node)
                    NEDepthwiseConvolutionLayer3x3>(*polymorphic_downcast<DepthwiseConvolutionLayerNode *>(node));
         case NodeType::DetectionOutputLayer:
             return detail::validate_detection_output_layer<CPPDetectionOutputLayer>(*polymorphic_downcast<DetectionOutputLayerNode *>(node));
-        case NodeType::GenerateProposalsLayer:
-            return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : GenerateProposalsLayer");
         case NodeType::NormalizePlanarYUVLayer:
             return ARM_COMPUTE_CREATE_ERROR(arm_compute::ErrorCode::RUNTIME_ERROR, "Unsupported operation : NormalizePlanarYUVLayer");
         case NodeType::PadLayer:
diff --git a/src/graph/nodes/GenerateProposalsLayerNode.cpp b/src/graph/nodes/GenerateProposalsLayerNode.cpp
deleted file mode 100644
index 7367e80539..0000000000
--- a/src/graph/nodes/GenerateProposalsLayerNode.cpp
+++ /dev/null
@@ -1,102 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "arm_compute/graph/nodes/GenerateProposalsLayerNode.h"
-
-#include "arm_compute/graph/Graph.h"
-#include "arm_compute/graph/INodeVisitor.h"
-
-#include "arm_compute/core/Helpers.h"
-
-namespace arm_compute
-{
-namespace graph
-{
-GenerateProposalsLayerNode::GenerateProposalsLayerNode(GenerateProposalsInfo &info)
-    : _info(info)
-{
-    _input_edges.resize(3, EmptyEdgeID);
-    _outputs.resize(3, NullTensorID);
-}
-
-const GenerateProposalsInfo &GenerateProposalsLayerNode::info() const
-{
-    return _info;
-}
-
-bool GenerateProposalsLayerNode::forward_descriptors()
-{
-    if((input_id(0) != NullTensorID) && (input_id(1) != NullTensorID) && (input_id(2) != NullTensorID) && (output_id(0) != NullTensorID) && (output_id(1) != NullTensorID)
-       && (output_id(2) != NullTensorID))
-    {
-        for(unsigned int i = 0; i < 3; ++i)
-        {
-            Tensor *dst = output(i);
-            ARM_COMPUTE_ERROR_ON(dst == nullptr);
-            dst->desc() = configure_output(i);
-        }
-        return true;
-    }
-    return false;
-}
-
-TensorDescriptor GenerateProposalsLayerNode::configure_output(size_t idx) const
-{
-    ARM_COMPUTE_ERROR_ON(idx > 3);
-
-    const Tensor *src = input(0);
-    ARM_COMPUTE_ERROR_ON(src == nullptr);
-    TensorDescriptor output_desc = src->desc();
-
-    switch(idx)
-    {
-        case 0:
-            // Configure proposals output
-            output_desc.shape = TensorShape(5, src->desc().shape.total_size());
-            break;
-        case 1:
-            // Configure scores_out output
-            output_desc.shape = TensorShape(src->desc().shape.total_size());
-            break;
-        case 2:
-            // Configure num_valid_proposals
-            output_desc.shape     = TensorShape(1);
-            output_desc.data_type = DataType::U32;
-            break;
-        default:
-            ARM_COMPUTE_ERROR("Unsupported output index");
-    }
-    return output_desc;
-}
-
-NodeType GenerateProposalsLayerNode::type() const
-{
-    return NodeType::GenerateProposalsLayer;
-}
-
-void GenerateProposalsLayerNode::accept(INodeVisitor &v)
-{
-    v.visit(*this);
-}
-} // namespace graph
-} // namespace arm_compute
diff --git a/src/runtime/CL/functions/CLComputeAllAnchors.cpp b/src/runtime/CL/functions/CLComputeAllAnchors.cpp
deleted file mode 100644
index 409d3c9e91..0000000000
--- a/src/runtime/CL/functions/CLComputeAllAnchors.cpp
+++ /dev/null
@@ -1,42 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h"
-
-#include "support/ToolchainSupport.h"
-
-namespace arm_compute
-{
-void CLComputeAllAnchors::configure(const ICLTensor *anchors, ICLTensor *all_anchors, const ComputeAnchorsInfo &info)
-{
-    // Configure ComputeAllAnchors kernel
-    auto k = arm_compute::support::cpp14::make_unique<CLComputeAllAnchorsKernel>();
-    k->configure(anchors, all_anchors, info);
-    _kernel = std::move(k);
-}
-
-Status CLComputeAllAnchors::validate(const ITensorInfo *anchors, const ITensorInfo *all_anchors, const ComputeAnchorsInfo &info)
-{
-    return CLComputeAllAnchorsKernel::validate(anchors, all_anchors, info);
-}
-} // namespace arm_compute
diff --git a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp b/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp
deleted file mode 100644
index c25a6c616e..0000000000
--- a/src/runtime/CL/functions/CLGenerateProposalsLayer.cpp
+++ /dev/null
@@ -1,284 +0,0 @@
-/*
- * Copyright (c) 2018-2019 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h"
-
-#include "arm_compute/core/CL/ICLTensor.h"
-#include "arm_compute/core/Types.h"
-#include "support/ToolchainSupport.h"
-
-namespace arm_compute
-{
-CLGenerateProposalsLayer::CLGenerateProposalsLayer(std::shared_ptr<IMemoryManager> memory_manager)
-    : _memory_group(std::move(memory_manager)),
-      _permute_deltas_kernel(),
-      _flatten_deltas_kernel(),
-      _permute_scores_kernel(),
-      _flatten_scores_kernel(),
-      _compute_anchors_kernel(),
-      _bounding_box_kernel(),
-      _memset_kernel(),
-      _padded_copy_kernel(),
-      _cpp_nms_kernel(),
-      _is_nhwc(false),
-      _deltas_permuted(),
-      _deltas_flattened(),
-      _scores_permuted(),
-      _scores_flattened(),
-      _all_anchors(),
-      _all_proposals(),
-      _keeps_nms_unused(),
-      _classes_nms_unused(),
-      _proposals_4_roi_values(),
-      _num_valid_proposals(nullptr),
-      _scores_out(nullptr)
-{
-}
-
-void CLGenerateProposalsLayer::configure(const ICLTensor *scores, const ICLTensor *deltas, const ICLTensor *anchors, ICLTensor *proposals, ICLTensor *scores_out, ICLTensor *num_valid_proposals,
-                                         const GenerateProposalsInfo &info)
-{
-    ARM_COMPUTE_ERROR_ON_NULLPTR(scores, deltas, anchors, proposals, scores_out, num_valid_proposals);
-    ARM_COMPUTE_ERROR_THROW_ON(CLGenerateProposalsLayer::validate(scores->info(), deltas->info(), anchors->info(), proposals->info(), scores_out->info(), num_valid_proposals->info(), info));
-
-    _is_nhwc                         = scores->info()->data_layout() == DataLayout::NHWC;
-    const DataType data_type         = deltas->info()->data_type();
-    const int      num_anchors       = scores->info()->dimension(get_data_layout_dimension_index(scores->info()->data_layout(), DataLayoutDimension::CHANNEL));
-    const int      feat_width        = scores->info()->dimension(get_data_layout_dimension_index(scores->info()->data_layout(), DataLayoutDimension::WIDTH));
-    const int      feat_height       = scores->info()->dimension(get_data_layout_dimension_index(scores->info()->data_layout(), DataLayoutDimension::HEIGHT));
-    const int      total_num_anchors = num_anchors * feat_width * feat_height;
-    const int      pre_nms_topN      = info.pre_nms_topN();
-    const int      post_nms_topN     = info.post_nms_topN();
-    const size_t   values_per_roi    = info.values_per_roi();
-
-    // Compute all the anchors
-    _memory_group.manage(&_all_anchors);
-    _compute_anchors_kernel.configure(anchors, &_all_anchors, ComputeAnchorsInfo(feat_width, feat_height, info.spatial_scale()));
-
-    const TensorShape flatten_shape_deltas(values_per_roi, total_num_anchors);
-    _deltas_flattened.allocator()->init(TensorInfo(flatten_shape_deltas, 1, data_type));
-
-    // Permute and reshape deltas
-    if(!_is_nhwc)
-    {
-        _memory_group.manage(&_deltas_permuted);
-        _memory_group.manage(&_deltas_flattened);
-        _permute_deltas_kernel.configure(deltas, &_deltas_permuted, PermutationVector{ 2, 0, 1 });
-        _flatten_deltas_kernel.configure(&_deltas_permuted, &_deltas_flattened);
-        _deltas_permuted.allocator()->allocate();
-    }
-    else
-    {
-        _memory_group.manage(&_deltas_flattened);
-        _flatten_deltas_kernel.configure(deltas, &_deltas_flattened);
-    }
-
-    const TensorShape flatten_shape_scores(1, total_num_anchors);
-    _scores_flattened.allocator()->init(TensorInfo(flatten_shape_scores, 1, data_type));
-
-    // Permute and reshape scores
-    if(!_is_nhwc)
-    {
-        _memory_group.manage(&_scores_permuted);
-        _memory_group.manage(&_scores_flattened);
-        _permute_scores_kernel.configure(scores, &_scores_permuted, PermutationVector{ 2, 0, 1 });
-        _flatten_scores_kernel.configure(&_scores_permuted, &_scores_flattened);
-        _scores_permuted.allocator()->allocate();
-    }
-    else
-    {
-        _memory_group.manage(&_scores_flattened);
-        _flatten_scores_kernel.configure(scores, &_scores_flattened);
-    }
-
-    // Bounding box transform
-    _memory_group.manage(&_all_proposals);
-    BoundingBoxTransformInfo bbox_info(info.im_width(), info.im_height(), 1.f);
-    _bounding_box_kernel.configure(&_all_anchors, &_all_proposals, &_deltas_flattened, bbox_info);
-    _deltas_flattened.allocator()->allocate();
-    _all_anchors.allocator()->allocate();
-
-    // The original layer implementation first selects the best pre_nms_topN anchors (thus having a lightweight sort)
-    // that are then transformed by bbox_transform. The boxes generated are then fed into a non-sorting NMS operation.
-    // Since we are reusing the NMS layer and we don't implement any CL/sort, we let NMS do the sorting (of all the input)
-    // and the filtering
-    const int   scores_nms_size = std::min<int>(std::min<int>(post_nms_topN, pre_nms_topN), total_num_anchors);
-    const float min_size_scaled = info.min_size() * info.im_scale();
-    _memory_group.manage(&_classes_nms_unused);
-    _memory_group.manage(&_keeps_nms_unused);
-
-    // Note that NMS needs outputs preinitialized.
-    auto_init_if_empty(*scores_out->info(), TensorShape(scores_nms_size), 1, data_type);
-    auto_init_if_empty(*_proposals_4_roi_values.info(), TensorShape(values_per_roi, scores_nms_size), 1, data_type);
-    auto_init_if_empty(*num_valid_proposals->info(), TensorShape(1), 1, DataType::U32);
-
-    // Initialize temporaries (unused) outputs
-    _classes_nms_unused.allocator()->init(TensorInfo(TensorShape(1, 1), 1, data_type));
-    _keeps_nms_unused.allocator()->init(*scores_out->info());
-
-    // Save the output (to map and unmap them at run)
-    _scores_out          = scores_out;
-    _num_valid_proposals = num_valid_proposals;
-
-    _memory_group.manage(&_proposals_4_roi_values);
-    _cpp_nms_kernel.configure(&_scores_flattened, &_all_proposals, nullptr, scores_out, &_proposals_4_roi_values, &_classes_nms_unused, nullptr, &_keeps_nms_unused, num_valid_proposals,
-                              BoxNMSLimitInfo(0.0f, info.nms_thres(), scores_nms_size, false, NMSType::LINEAR, 0.5f, 0.001f, true, min_size_scaled, info.im_width(), info.im_height()));
-    _keeps_nms_unused.allocator()->allocate();
-    _classes_nms_unused.allocator()->allocate();
-    _all_proposals.allocator()->allocate();
-    _scores_flattened.allocator()->allocate();
-
-    // Add the first column that represents the batch id. This will be all zeros, as we don't support multiple images
-    _padded_copy_kernel.configure(&_proposals_4_roi_values, proposals, PaddingList{ { 1, 0 } });
-    _proposals_4_roi_values.allocator()->allocate();
-
-    _memset_kernel.configure(proposals, PixelValue());
-}
-
-Status CLGenerateProposalsLayer::validate(const ITensorInfo *scores, const ITensorInfo *deltas, const ITensorInfo *anchors, const ITensorInfo *proposals, const ITensorInfo *scores_out,
-                                          const ITensorInfo *num_valid_proposals, const GenerateProposalsInfo &info)
-{
-    ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(scores, deltas, anchors, proposals, scores_out, num_valid_proposals);
-    ARM_COMPUTE_RETURN_ERROR_ON_DATA_LAYOUT_NOT_IN(scores, DataLayout::NCHW, DataLayout::NHWC);
-    ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_LAYOUT(scores, deltas);
-
-    const int num_anchors       = scores->dimension(get_data_layout_dimension_index(scores->data_layout(), DataLayoutDimension::CHANNEL));
-    const int feat_width        = scores->dimension(get_data_layout_dimension_index(scores->data_layout(), DataLayoutDimension::WIDTH));
-    const int feat_height       = scores->dimension(get_data_layout_dimension_index(scores->data_layout(), DataLayoutDimension::HEIGHT));
-    const int num_images        = scores->dimension(3);
-    const int total_num_anchors = num_anchors * feat_width * feat_height;
-    const int values_per_roi    = info.values_per_roi();
-
-    ARM_COMPUTE_RETURN_ERROR_ON(num_images > 1);
-
-    TensorInfo all_anchors_info(anchors->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true));
-    ARM_COMPUTE_RETURN_ON_ERROR(CLComputeAllAnchorsKernel::validate(anchors, &all_anchors_info, ComputeAnchorsInfo(feat_width, feat_height, info.spatial_scale())));
-
-    TensorInfo deltas_permuted_info = deltas->clone()->set_tensor_shape(TensorShape(values_per_roi * num_anchors, feat_width, feat_height)).set_is_resizable(true);
-    TensorInfo scores_permuted_info = scores->clone()->set_tensor_shape(TensorShape(num_anchors, feat_width, feat_height)).set_is_resizable(true);
-    if(scores->data_layout() == DataLayout::NHWC)
-    {
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(deltas, &deltas_permuted_info);
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(scores, &scores_permuted_info);
-    }
-    else
-    {
-        ARM_COMPUTE_RETURN_ON_ERROR(CLPermuteKernel::validate(deltas, &deltas_permuted_info, PermutationVector{ 2, 0, 1 }));
-        ARM_COMPUTE_RETURN_ON_ERROR(CLPermuteKernel::validate(scores, &scores_permuted_info, PermutationVector{ 2, 0, 1 }));
-    }
-
-    TensorInfo deltas_flattened_info(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true));
-    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&deltas_permuted_info, &deltas_flattened_info));
-
-    TensorInfo scores_flattened_info(deltas->clone()->set_tensor_shape(TensorShape(1, total_num_anchors)).set_is_resizable(true));
-    TensorInfo proposals_4_roi_values(deltas->clone()->set_tensor_shape(TensorShape(values_per_roi, total_num_anchors)).set_is_resizable(true));
-
-    ARM_COMPUTE_RETURN_ON_ERROR(CLReshapeLayerKernel::validate(&scores_permuted_info, &scores_flattened_info));
-    ARM_COMPUTE_RETURN_ON_ERROR(CLBoundingBoxTransformKernel::validate(&all_anchors_info, &proposals_4_roi_values, &deltas_flattened_info, BoundingBoxTransformInfo(info.im_width(), info.im_height(),
-                                                                       1.f)));
-
-    ARM_COMPUTE_RETURN_ON_ERROR(CLCopyKernel::validate(&proposals_4_roi_values, proposals, PaddingList{ { 0, 1 } }));
-    ARM_COMPUTE_RETURN_ON_ERROR(CLMemsetKernel::validate(proposals, PixelValue()));
-
-    if(num_valid_proposals->total_size() > 0)
-    {
-        ARM_COMPUTE_RETURN_ERROR_ON(num_valid_proposals->num_dimensions() > 1);
-        ARM_COMPUTE_RETURN_ERROR_ON(num_valid_proposals->dimension(0) > 1);
-        ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(num_valid_proposals, 1, DataType::U32);
-    }
-
-    if(proposals->total_size() > 0)
-    {
-        ARM_COMPUTE_RETURN_ERROR_ON(proposals->num_dimensions() > 2);
-        ARM_COMPUTE_RETURN_ERROR_ON(proposals->dimension(0) != size_t(values_per_roi) + 1);
-        ARM_COMPUTE_RETURN_ERROR_ON(proposals->dimension(1) != size_t(total_num_anchors));
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(proposals, deltas);
-    }
-
-    if(scores_out->total_size() > 0)
-    {
-        ARM_COMPUTE_RETURN_ERROR_ON(scores_out->num_dimensions() > 1);
-        ARM_COMPUTE_RETURN_ERROR_ON(scores_out->dimension(0) != size_t(total_num_anchors));
-        ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(scores_out, scores);
-    }
-
-    return Status{};
-}
-
-void CLGenerateProposalsLayer::run_cpp_nms_kernel()
-{
-    // Map inputs
-    _scores_flattened.map(true);
-    _all_proposals.map(true);
-
-    // Map outputs
-    _scores_out->map(CLScheduler::get().queue(), true);
-    _proposals_4_roi_values.map(CLScheduler::get().queue(), true);
-    _num_valid_proposals->map(CLScheduler::get().queue(), true);
-    _keeps_nms_unused.map(true);
-    _classes_nms_unused.map(true);
-
-    // Run nms
-    CPPScheduler::get().schedule(&_cpp_nms_kernel, Window::DimX);
-
-    // Unmap outputs
-    _keeps_nms_unused.unmap();
-    _classes_nms_unused.unmap();
-    _scores_out->unmap(CLScheduler::get().queue());
-    _proposals_4_roi_values.unmap(CLScheduler::get().queue());
-    _num_valid_proposals->unmap(CLScheduler::get().queue());
-
-    // Unmap inputs
-    _scores_flattened.unmap();
-    _all_proposals.unmap();
-}
-
-void CLGenerateProposalsLayer::run()
-{
-    // Acquire all the temporaries
-    _memory_group.acquire();
-
-    // Compute all the anchors
-    CLScheduler::get().enqueue(_compute_anchors_kernel, false);
-
-    // Transpose and reshape the inputs
-    if(!_is_nhwc)
-    {
-        CLScheduler::get().enqueue(_permute_deltas_kernel, false);
-        CLScheduler::get().enqueue(_permute_scores_kernel, false);
-    }
-    CLScheduler::get().enqueue(_flatten_deltas_kernel, false);
-    CLScheduler::get().enqueue(_flatten_scores_kernel, false);
-
-    // Build the boxes
-    CLScheduler::get().enqueue(_bounding_box_kernel, false);
-    // Non maxima suppression
-    run_cpp_nms_kernel();
-    // Add dummy batch indexes
-    CLScheduler::get().enqueue(_memset_kernel, true);
-    CLScheduler::get().enqueue(_padded_copy_kernel, true);
-
-    // Release all the temporaries
-    _memory_group.release();
-}
-} // namespace arm_compute
diff --git a/tests/validation/CL/GenerateProposalsLayer.cpp b/tests/validation/CL/GenerateProposalsLayer.cpp
deleted file mode 100644
index ac2d0ef969..0000000000
--- a/tests/validation/CL/GenerateProposalsLayer.cpp
+++ /dev/null
@@ -1,375 +0,0 @@
-/*
- * Copyright (c) 2018-2019 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "arm_compute/runtime/CL/CLScheduler.h"
-#include "arm_compute/runtime/CL/functions/CLComputeAllAnchors.h"
-#include "arm_compute/runtime/CL/functions/CLGenerateProposalsLayer.h"
-#include "arm_compute/runtime/CL/functions/CLPermute.h"
-#include "arm_compute/runtime/CL/functions/CLSlice.h"
-#include "tests/CL/CLAccessor.h"
-#include "tests/CL/CLArrayAccessor.h"
-#include "tests/Globals.h"
-#include "tests/framework/Macros.h"
-#include "tests/framework/datasets/Datasets.h"
-#include "tests/validation/Validation.h"
-#include "tests/validation/fixtures/ComputeAllAnchorsFixture.h"
-#include "utils/TypePrinter.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-namespace
-{
-template <typename U, typename T>
-inline void fill_tensor(U &&tensor, const std::vector<T> &v)
-{
-    std::memcpy(tensor.data(), v.data(), sizeof(T) * v.size());
-}
-
-template <typename T>
-inline void fill_tensor(CLAccessor &&tensor, const std::vector<T> &v)
-{
-    if(tensor.data_layout() == DataLayout::NCHW)
-    {
-        std::memcpy(tensor.data(), v.data(), sizeof(T) * v.size());
-    }
-    else
-    {
-        const int channels = tensor.shape()[0];
-        const int width    = tensor.shape()[1];
-        const int height   = tensor.shape()[2];
-        for(int x = 0; x < width; ++x)
-        {
-            for(int y = 0; y < height; ++y)
-            {
-                for(int c = 0; c < channels; ++c)
-                {
-                    *(reinterpret_cast<T *>(tensor(Coordinates(c, x, y)))) = *(reinterpret_cast<const T *>(v.data() + x + y * width + c * height * width));
-                }
-            }
-        }
-    }
-}
-
-const auto ComputeAllInfoDataset = framework::dataset::make("ComputeAllInfo",
-{
-    ComputeAnchorsInfo(10U, 10U, 1. / 16.f),
-    ComputeAnchorsInfo(100U, 1U, 1. / 2.f),
-    ComputeAnchorsInfo(100U, 1U, 1. / 4.f),
-    ComputeAnchorsInfo(100U, 100U, 1. / 4.f),
-
-});
-} // namespace
-
-TEST_SUITE(CL)
-TEST_SUITE(GenerateProposals)
-
-// *INDENT-OFF*
-// clang-format off
-DATA_TEST_CASE(Validate, framework::DatasetMode::ALL, zip(zip(zip(zip(zip(zip(zip(
-               framework::dataset::make("scores", { TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F32),
-                                                    TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Mismatching types
-                                                    TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Wrong deltas (number of transformation non multiple of 4)
-                                                    TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Wrong anchors (number of values per roi != 5)
-                                                    TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16), // Output tensor num_valid_proposals not scalar
-                                                    TensorInfo(TensorShape(100U, 100U, 9U), 1, DataType::F16)}), // num_valid_proposals not U32
-               framework::dataset::make("deltas",{ TensorInfo(TensorShape(100U, 100U, 36U), 1, DataType::F32),
-                                                   TensorInfo(TensorShape(100U, 100U, 36U), 1, DataType::F32),
-                                                   TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32),
-                                                   TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32),
-                                                   TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32),
-                                                   TensorInfo(TensorShape(100U, 100U, 38U), 1, DataType::F32)})),
-               framework::dataset::make("anchors", { TensorInfo(TensorShape(4U, 9U), 1, DataType::F32),
-                                                     TensorInfo(TensorShape(4U, 9U), 1, DataType::F32),
-                                                     TensorInfo(TensorShape(4U, 9U), 1, DataType::F32),
-                                                     TensorInfo(TensorShape(5U, 9U), 1, DataType::F32),
-                                                     TensorInfo(TensorShape(4U, 9U), 1, DataType::F32),
-                                                     TensorInfo(TensorShape(4U, 9U), 1, DataType::F32)})),
-               framework::dataset::make("proposals", { TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32),
-                                                       TensorInfo(TensorShape(5U, 100U*100U*9U), 1, DataType::F32)})),
-               framework::dataset::make("scores_out", { TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32),
-                                                        TensorInfo(TensorShape(100U*100U*9U), 1, DataType::F32)})),
-               framework::dataset::make("num_valid_proposals", { TensorInfo(TensorShape(1U, 1U), 1, DataType::U32),
-                                                                 TensorInfo(TensorShape(1U, 1U), 1, DataType::U32),
-                                                                 TensorInfo(TensorShape(1U, 1U), 1, DataType::U32),
-                                                                 TensorInfo(TensorShape(1U, 1U), 1, DataType::U32),
-                                                                 TensorInfo(TensorShape(1U, 10U), 1, DataType::U32),
-                                                                 TensorInfo(TensorShape(1U, 1U), 1, DataType::F16)})),
-               framework::dataset::make("generate_proposals_info", { GenerateProposalsInfo(10.f, 10.f, 1.f),
-                                                                     GenerateProposalsInfo(10.f, 10.f, 1.f),
-                                                                     GenerateProposalsInfo(10.f, 10.f, 1.f),
-                                                                     GenerateProposalsInfo(10.f, 10.f, 1.f),
-                                                                     GenerateProposalsInfo(10.f, 10.f, 1.f),
-                                                                     GenerateProposalsInfo(10.f, 10.f, 1.f)})),
-               framework::dataset::make("Expected", { true, false, false, false, false, false })),
-        scores, deltas, anchors, proposals, scores_out, num_valid_proposals, generate_proposals_info, expected)
-{
-    ARM_COMPUTE_EXPECT(bool(CLGenerateProposalsLayer::validate(&scores.clone()->set_is_resizable(true),
-                                                          &deltas.clone()->set_is_resizable(true),
-                                                          &anchors.clone()->set_is_resizable(true),
-                                                          &proposals.clone()->set_is_resizable(true),
-                                                          &scores_out.clone()->set_is_resizable(true),
-                                                          &num_valid_proposals.clone()->set_is_resizable(true),
-                                                          generate_proposals_info)) == expected, framework::LogLevel::ERRORS);
-}
-// clang-format on
-// *INDENT-ON*
-
-template <typename T>
-using CLComputeAllAnchorsFixture = ComputeAllAnchorsFixture<CLTensor, CLAccessor, CLComputeAllAnchors, T>;
-
-TEST_SUITE(Float)
-TEST_SUITE(FP32)
-DATA_TEST_CASE(IntegrationTestCaseAllAnchors, framework::DatasetMode::ALL, framework::dataset::make("DataType", { DataType::F32 }),
-               data_type)
-{
-    const int values_per_roi = 4;
-    const int num_anchors    = 3;
-    const int feature_height = 4;
-    const int feature_width  = 3;
-
-    SimpleTensor<float> anchors_expected(TensorShape(values_per_roi, feature_width * feature_height * num_anchors), DataType::F32);
-    fill_tensor(anchors_expected, std::vector<float> { -38, -16, 53, 31, -84, -40, 99, 55, -176, -88, 191, 103,
-                                                       -22, -16, 69, 31, -68, -40, 115, 55, -160, -88, 207, 103,
-                                                       -6, -16, 85, 31, -52, -40, 131, 55, -144, -88, 223, 103, -38,
-                                                       0, 53, 47, -84, -24, 99, 71,
-                                                       -176, -72, 191, 119, -22, 0, 69, 47, -68, -24, 115, 71, -160, -72, 207,
-                                                       119, -6, 0, 85, 47, -52, -24, 131, 71, -144, -72, 223, 119, -38, 16, 53,
-                                                       63, -84, -8, 99, 87, -176, -56, 191, 135, -22, 16, 69, 63, -68, -8, 115,
-                                                       87, -160, -56, 207, 135, -6, 16, 85, 63, -52, -8, 131, 87, -144, -56, 223,
-                                                       135, -38, 32, 53, 79, -84, 8, 99, 103, -176, -40, 191, 151, -22, 32, 69,
-                                                       79, -68, 8, 115, 103, -160, -40, 207, 151, -6, 32, 85, 79, -52, 8, 131,
-                                                       103, -144, -40, 223, 151
-                                                     });
-
-    CLTensor all_anchors;
-    CLTensor anchors = create_tensor<CLTensor>(TensorShape(4, num_anchors), data_type);
-
-    // Create and configure function
-    CLComputeAllAnchors compute_anchors;
-    compute_anchors.configure(&anchors, &all_anchors, ComputeAnchorsInfo(feature_width, feature_height, 1. / 16.0));
-    anchors.allocator()->allocate();
-    all_anchors.allocator()->allocate();
-
-    fill_tensor(CLAccessor(anchors), std::vector<float> { -38, -16, 53, 31,
-                                                          -84, -40, 99, 55,
-                                                          -176, -88, 191, 103
-                                                        });
-    // Compute function
-    compute_anchors.run();
-    validate(CLAccessor(all_anchors), anchors_expected);
-}
-
-DATA_TEST_CASE(IntegrationTestCaseGenerateProposals, framework::DatasetMode::ALL, combine(framework::dataset::make("DataType", { DataType::F32 }),
-                                                                                          framework::dataset::make("DataLayout", { DataLayout::NCHW, DataLayout::NHWC })),
-               data_type, data_layout)
-{
-    const int values_per_roi = 4;
-    const int num_anchors    = 2;
-    const int feature_height = 4;
-    const int feature_width  = 5;
-
-    std::vector<float> scores_vector
-    {
-        5.44218998e-03f, 1.19207997e-03f, 1.12379994e-03f, 1.17181998e-03f,
-        1.20544003e-03f, 6.17993006e-04f, 1.05261997e-05f, 8.91025957e-06f,
-        9.29536981e-09f, 6.09605013e-05f, 4.72735002e-04f, 1.13482002e-10f,
-        1.50015003e-05f, 4.45032993e-06f, 3.21612994e-08f, 8.02662980e-04f,
-        1.40488002e-04f, 3.12508007e-07f, 3.02616991e-06f, 1.97759000e-08f,
-        2.66913995e-02f, 5.26766013e-03f, 5.05053019e-03f, 5.62100019e-03f,
-        5.37420018e-03f, 5.26280981e-03f, 2.48894998e-04f, 1.06842002e-04f,
-        3.92931997e-06f, 1.79388002e-03f, 4.79440019e-03f, 3.41609990e-07f,
-        5.20430971e-04f, 3.34090000e-05f, 2.19159006e-07f, 2.28786003e-03f,
-        5.16703985e-05f, 4.04523007e-06f, 1.79227004e-06f, 5.32449000e-08f
-    };
-
-    std::vector<float> bbx_vector
-    {
-        -1.65040009e-02f, -1.84051003e-02f, -1.85930002e-02f, -2.08263006e-02f,
-        -1.83814000e-02f, -2.89172009e-02f, -3.89706008e-02f, -7.52277970e-02f,
-        -1.54091999e-01f, -2.55433004e-02f, -1.77490003e-02f, -1.10340998e-01f,
-        -4.20190990e-02f, -2.71421000e-02f, 6.89801015e-03f, 5.71171008e-02f,
-        -1.75665006e-01f, 2.30021998e-02f, 3.08554992e-02f, -1.39333997e-02f,
-        3.40579003e-01f, 3.91070992e-01f, 3.91624004e-01f, 3.92527014e-01f,
-        3.91445011e-01f, 3.79328012e-01f, 4.26631987e-01f, 3.64892989e-01f,
-        2.76894987e-01f, 5.13985991e-01f, 3.79999995e-01f, 1.80457994e-01f,
-        4.37402993e-01f, 4.18545991e-01f, 2.51549989e-01f, 4.48318988e-01f,
-        1.68564007e-01f, 4.65440989e-01f, 4.21891987e-01f, 4.45928007e-01f,
-        3.27155995e-03f, 3.71480011e-03f, 3.60032008e-03f, 4.27092984e-03f,
-        3.74579988e-03f, 5.95752988e-03f, -3.14473989e-03f, 3.52022005e-03f,
-        -1.88564006e-02f, 1.65188999e-03f, 1.73791999e-03f, -3.56074013e-02f,
-        -1.66615995e-04f, 3.14146001e-03f, -1.11830998e-02f, -5.35363983e-03f,
-        6.49790000e-03f, -9.27671045e-03f, -2.83346009e-02f, -1.61233004e-02f,
-        -2.15505004e-01f, -2.19910994e-01f, -2.20872998e-01f, -2.12831005e-01f,
-        -2.19145000e-01f, -2.27687001e-01f, -3.43973994e-01f, -2.75869995e-01f,
-        -3.19516987e-01f, -2.50418007e-01f, -2.48537004e-01f, -5.08224010e-01f,
-        -2.28724003e-01f, -2.82402009e-01f, -3.75815988e-01f, -2.86352992e-01f,
-        -5.28333001e-02f, -4.43836004e-01f, -4.55134988e-01f, -4.34897989e-01f,
-        -5.65053988e-03f, -9.25739005e-04f, -1.06790999e-03f, -2.37016007e-03f,
-        -9.71166010e-04f, -8.90910998e-03f, -1.17592998e-02f, -2.08992008e-02f,
-        -4.94231991e-02f, 6.63906988e-03f, 3.20469006e-03f, -6.44695014e-02f,
-        -3.11607006e-03f, 2.02738005e-03f, 1.48096997e-02f, 4.39785011e-02f,
-        -8.28424022e-02f, 3.62076014e-02f, 2.71668993e-02f, 1.38250999e-02f,
-        6.76669031e-02f, 1.03252999e-01f, 1.03255004e-01f, 9.89722982e-02f,
-        1.03646003e-01f, 4.79663983e-02f, 1.11014001e-01f, 9.31736007e-02f,
-        1.15768999e-01f, 1.04014002e-01f, -8.90677981e-03f, 1.13103002e-01f,
-        1.33085996e-01f, 1.25405997e-01f, 1.50051996e-01f, -1.13038003e-01f,
-        7.01059997e-02f, 1.79651007e-01f, 1.41055003e-01f, 1.62841007e-01f,
-        -1.00247003e-02f, -8.17587040e-03f, -8.32176022e-03f, -8.90108012e-03f,
-        -8.13035015e-03f, -1.77263003e-02f, -3.69572006e-02f, -3.51580009e-02f,
-        -5.92143014e-02f, -1.80795006e-02f, -5.46086021e-03f, -4.10550982e-02f,
-        -1.83081999e-02f, -2.15411000e-02f, -1.17953997e-02f, 3.33894007e-02f,
-        -5.29635996e-02f, -6.97528012e-03f, -3.15250992e-03f, -3.27355005e-02f,
-        1.29676998e-01f, 1.16080999e-01f, 1.15947001e-01f, 1.21797003e-01f,
-        1.16089001e-01f, 1.44875005e-01f, 1.15617000e-01f, 1.31586999e-01f,
-        1.74735002e-02f, 1.21973999e-01f, 1.31596997e-01f, 2.48907991e-02f,
-        6.18605018e-02f, 1.12855002e-01f, -6.99798986e-02f, 9.58312973e-02f,
-        1.53593004e-01f, -8.75087008e-02f, -4.92327996e-02f, -3.32239009e-02f
-    };
-
-    std::vector<float> anchors_vector{ -38, -16, 53, 31,
-                                       -120, -120, 135, 135 };
-
-    SimpleTensor<float> proposals_expected(TensorShape(5, 9), DataType::F32);
-    fill_tensor(proposals_expected, std::vector<float> { 0, 0, 0, 79, 59,
-                                                         0, 0, 5.0005703f, 52.63237f, 43.69501495f,
-                                                         0, 24.13628387f, 7.51243401f, 79, 46.06628418f,
-                                                         0, 0, 7.50924301f, 68.47792816f, 46.03357315f,
-                                                         0, 0, 23.09477997f, 51.61448669f, 59,
-                                                         0, 0, 39.52141571f, 52.44710541f, 59,
-                                                         0, 23.57396317f, 29.98791885f, 79, 59,
-                                                         0, 0, 41.90219116f, 79, 59,
-                                                         0, 0, 23.30098343f, 79, 59
-                                                       });
-
-    SimpleTensor<float> scores_expected(TensorShape(9), DataType::F32);
-    fill_tensor(scores_expected, std::vector<float>
-    {
-        2.66913995e-02f,
-        5.44218998e-03f,
-        1.20544003e-03f,
-        1.19207997e-03f,
-        6.17993006e-04f,
-        4.72735002e-04f,
-        6.09605013e-05f,
-        1.50015003e-05f,
-        8.91025957e-06f
-    });
-
-    TensorShape scores_shape = TensorShape(feature_width, feature_height, num_anchors);
-    TensorShape deltas_shape = TensorShape(feature_width, feature_height, values_per_roi * num_anchors);
-    if(data_layout == DataLayout::NHWC)
-    {
-        permute(scores_shape, PermutationVector(2U, 0U, 1U));
-        permute(deltas_shape, PermutationVector(2U, 0U, 1U));
-    }
-
-    // Inputs
-    CLTensor scores      = create_tensor<CLTensor>(scores_shape, data_type, 1, QuantizationInfo(), data_layout);
-    CLTensor bbox_deltas = create_tensor<CLTensor>(deltas_shape, data_type, 1, QuantizationInfo(), data_layout);
-    CLTensor anchors     = create_tensor<CLTensor>(TensorShape(values_per_roi, num_anchors), data_type);
-
-    // Outputs
-    CLTensor proposals;
-    CLTensor num_valid_proposals;
-    CLTensor scores_out;
-    num_valid_proposals.allocator()->init(TensorInfo(TensorShape(1), 1, DataType::U32));
-
-    CLGenerateProposalsLayer generate_proposals;
-    generate_proposals.configure(&scores, &bbox_deltas, &anchors, &proposals, &scores_out, &num_valid_proposals,
-                                 GenerateProposalsInfo(80, 60, 0.166667f, 1 / 16.0, 6000, 300, 0.7f, 16.0f));
-
-    // Allocate memory for input/output tensors
-    scores.allocator()->allocate();
-    bbox_deltas.allocator()->allocate();
-    anchors.allocator()->allocate();
-    proposals.allocator()->allocate();
-    num_valid_proposals.allocator()->allocate();
-    scores_out.allocator()->allocate();
-    // Fill inputs
-    fill_tensor(CLAccessor(scores), scores_vector);
-    fill_tensor(CLAccessor(bbox_deltas), bbx_vector);
-    fill_tensor(CLAccessor(anchors), anchors_vector);
-
-    // Run operator
-    generate_proposals.run();
-    // Gather num_valid_proposals
-    num_valid_proposals.map();
-    const uint32_t N = *reinterpret_cast<uint32_t *>(num_valid_proposals.ptr_to_element(Coordinates(0, 0)));
-    num_valid_proposals.unmap();
-
-    // Select the first N entries of the proposals
-    CLTensor proposals_final;
-    CLSlice  select_proposals;
-    select_proposals.configure(&proposals, &proposals_final, Coordinates(0, 0), Coordinates(values_per_roi + 1, N));
-    proposals_final.allocator()->allocate();
-    select_proposals.run();
-
-    // Select the first N entries of the proposals
-    CLTensor scores_final;
-    CLSlice  select_scores;
-    select_scores.configure(&scores_out, &scores_final, Coordinates(0), Coordinates(N));
-    scores_final.allocator()->allocate();
-    select_scores.run();
-
-    const RelativeTolerance<float> tolerance_f32(1e-6f);
-    // Validate the output
-    validate(CLAccessor(proposals_final), proposals_expected, tolerance_f32);
-    validate(CLAccessor(scores_final), scores_expected, tolerance_f32);
-}
-
-FIXTURE_DATA_TEST_CASE(ComputeAllAnchors, CLComputeAllAnchorsFixture<float>, framework::DatasetMode::ALL,
-                       combine(combine(framework::dataset::make("NumAnchors", { 2, 4, 8 }), ComputeAllInfoDataset), framework::dataset::make("DataType", { DataType::F32 })))
-{
-    // Validate output
-    validate(CLAccessor(_target), _reference);
-}
-TEST_SUITE_END() // FP32
-
-TEST_SUITE(FP16)
-FIXTURE_DATA_TEST_CASE(ComputeAllAnchors, CLComputeAllAnchorsFixture<half>, framework::DatasetMode::ALL,
-                       combine(combine(framework::dataset::make("NumAnchors", { 2, 4, 8 }), ComputeAllInfoDataset), framework::dataset::make("DataType", { DataType::F16 })))
-{
-    // Validate output
-    validate(CLAccessor(_target), _reference);
-}
-TEST_SUITE_END() // FP16
-TEST_SUITE_END() // Float
-
-TEST_SUITE_END() // GenerateProposals
-TEST_SUITE_END() // CL
-
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/validation/fixtures/ComputeAllAnchorsFixture.h b/tests/validation/fixtures/ComputeAllAnchorsFixture.h
deleted file mode 100644
index f82cac4fe6..0000000000
--- a/tests/validation/fixtures/ComputeAllAnchorsFixture.h
+++ /dev/null
@@ -1,107 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef ARM_COMPUTE_TEST_COMPUTEALLANCHORS_FIXTURE
-#define ARM_COMPUTE_TEST_COMPUTEALLANCHORS_FIXTURE
-
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/core/Types.h"
-#include "tests/AssetsLibrary.h"
-#include "tests/Globals.h"
-#include "tests/IAccessor.h"
-#include "tests/framework/Asserts.h"
-#include "tests/framework/Fixture.h"
-#include "tests/validation/Helpers.h"
-#include "tests/validation/reference/ComputeAllAnchors.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-template <typename TensorType, typename AccessorType, typename FunctionType, typename T>
-class ComputeAllAnchorsFixture : public framework::Fixture
-{
-public:
-    template <typename...>
-    void setup(size_t num_anchors, const ComputeAnchorsInfo &info, DataType data_type)
-    {
-        _target    = compute_target(num_anchors, data_type, info);
-        _reference = compute_reference(num_anchors, data_type, info);
-    }
-
-protected:
-    template <typename U>
-    void fill(U &&tensor)
-    {
-        library->fill_tensor_uniform(tensor, 0, T(0), T(100));
-    }
-
-    TensorType compute_target(size_t num_anchors, DataType data_type, const ComputeAnchorsInfo &info)
-    {
-        // Create tensors
-        TensorShape anchors_shape(4, num_anchors);
-        TensorType  anchors = create_tensor<TensorType>(anchors_shape, data_type);
-        TensorType  all_anchors;
-
-        // Create and configure function
-        FunctionType compute_all_anchors;
-        compute_all_anchors.configure(&anchors, &all_anchors, info);
-
-        ARM_COMPUTE_EXPECT(all_anchors.info()->is_resizable(), framework::LogLevel::ERRORS);
-
-        // Allocate tensors
-        all_anchors.allocator()->allocate();
-        anchors.allocator()->allocate();
-
-        ARM_COMPUTE_EXPECT(!all_anchors.info()->is_resizable(), framework::LogLevel::ERRORS);
-
-        // Fill tensors
-        fill(CLAccessor(anchors));
-
-        // Compute function
-        compute_all_anchors.run();
-
-        return all_anchors;
-    }
-
-    SimpleTensor<T> compute_reference(size_t                    num_anchors,
-                                      DataType                  data_type,
-                                      const ComputeAnchorsInfo &info)
-    {
-        // Create reference tensor
-        SimpleTensor<T> anchors(TensorShape(4, num_anchors), data_type);
-
-        // Fill reference tensor
-        fill(anchors);
-        return reference::compute_all_anchors(anchors, info);
-    }
-
-    TensorType      _target{};
-    SimpleTensor<T> _reference{};
-};
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_COMPUTEALLANCHORS_FIXTURE */
diff --git a/tests/validation/reference/ComputeAllAnchors.cpp b/tests/validation/reference/ComputeAllAnchors.cpp
deleted file mode 100644
index 48f4767fae..0000000000
--- a/tests/validation/reference/ComputeAllAnchors.cpp
+++ /dev/null
@@ -1,79 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#include "ComputeAllAnchors.h"
-
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "arm_compute/core/utils/misc/Utility.h"
-#include "tests/validation/Helpers.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-namespace reference
-{
-template <typename T>
-SimpleTensor<T> compute_all_anchors(const SimpleTensor<T> &anchors, const ComputeAnchorsInfo &info)
-{
-    const int   num_anchors = anchors.shape()[1];
-    const auto  width       = int(info.feat_width());
-    const auto  height      = int(info.feat_height());
-    const float stride      = 1. / info.spatial_scale();
-
-    SimpleTensor<T> all_anchors(TensorShape(4, width * height * num_anchors), anchors.data_type());
-    const T        *anchors_ptr     = anchors.data();
-    T              *all_anchors_ptr = all_anchors.data();
-
-    // Iterate over the input grid and anchors
-    for(int y = 0; y < height; y++)
-    {
-        for(int x = 0; x < width; x++)
-        {
-            for(int a = 0; a < num_anchors; a++)
-            {
-                const T      shift_x   = T(x) * T(stride);
-                const T      shift_y   = T(y) * T(stride);
-                const size_t anchor_id = a + x * num_anchors + y * width * num_anchors;
-                // x1
-                all_anchors_ptr[anchor_id * 4] = anchors_ptr[4 * a] + shift_x;
-                // y1
-                all_anchors_ptr[anchor_id * 4 + 1] = anchors_ptr[4 * a + 1] + shift_y;
-                // x2
-                all_anchors_ptr[anchor_id * 4 + 2] = anchors_ptr[4 * a + 2] + shift_x;
-                // y2
-                all_anchors_ptr[anchor_id * 4 + 3] = anchors_ptr[4 * a + 3] + shift_y;
-            }
-        }
-    }
-    return all_anchors;
-}
-template SimpleTensor<float> compute_all_anchors(const SimpleTensor<float> &anchors, const ComputeAnchorsInfo &info);
-template SimpleTensor<half> compute_all_anchors(const SimpleTensor<half> &anchors, const ComputeAnchorsInfo &info);
-} // namespace reference
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
diff --git a/tests/validation/reference/ComputeAllAnchors.h b/tests/validation/reference/ComputeAllAnchors.h
deleted file mode 100644
index b21bf3cc7e..0000000000
--- a/tests/validation/reference/ComputeAllAnchors.h
+++ /dev/null
@@ -1,45 +0,0 @@
-/*
- * Copyright (c) 2018 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef __ARM_COMPUTE_TEST_COMPUTEALLANCHORS_H__
-#define __ARM_COMPUTE_TEST_COMPUTEALLANCHORS_H__
-
-#include "arm_compute/core/Types.h"
-#include "arm_compute/core/utils/misc/ShapeCalculator.h"
-#include "tests/validation/Helpers.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace validation
-{
-namespace reference
-{
-template <typename T>
-SimpleTensor<T> compute_all_anchors(const SimpleTensor<T> &anchors, const ComputeAnchorsInfo &info);
-} // namespace reference
-} // namespace validation
-} // namespace test
-} // namespace arm_compute
-#endif /* __ARM_COMPUTE_TEST_COMPUTEALLANCHORS_H__ */
diff --git a/utils/TypePrinter.h b/utils/TypePrinter.h
index f2cf606a00..3361c39ee3 100644
--- a/utils/TypePrinter.h
+++ b/utils/TypePrinter.h
@@ -261,58 +261,6 @@ inline std::string to_string(const BoundingBoxTransformInfo &bbox_info)
     return str.str();
 }
 
-/** Formatted output of the ComputeAnchorsInfo type.
- *
- * @param[out] os           Output stream.
- * @param[in]  anchors_info Type to output.
- *
- * @return Modified output stream.
- */
-inline ::std::ostream &operator<<(::std::ostream &os, const ComputeAnchorsInfo &anchors_info)
-{
-    os << "(" << anchors_info.feat_width() << "x" << anchors_info.feat_height() << ")~" << anchors_info.spatial_scale();
-    return os;
-}
-
-/** Formatted output of the ComputeAnchorsInfo type.
- *
- * @param[in] anchors_info Type to output.
- *
- * @return Formatted string.
- */
-inline std::string to_string(const ComputeAnchorsInfo &anchors_info)
-{
-    std::stringstream str;
-    str << anchors_info;
-    return str.str();
-}
-
-/** Formatted output of the GenerateProposalsInfo type.
- *
- * @param[out] os             Output stream.
- * @param[in]  proposals_info Type to output.
- *
- * @return Modified output stream.
- */
-inline ::std::ostream &operator<<(::std::ostream &os, const GenerateProposalsInfo &proposals_info)
-{
-    os << "(" << proposals_info.im_width() << "x" << proposals_info.im_height() << ")~" << proposals_info.im_scale();
-    return os;
-}
-
-/** Formatted output of the GenerateProposalsInfo type.
- *
- * @param[in] proposals_info Type to output.
- *
- * @return Formatted string.
- */
-inline std::string to_string(const GenerateProposalsInfo &proposals_info)
-{
-    std::stringstream str;
-    str << proposals_info;
-    return str.str();
-}
-
 /** Formatted output of the QuantizationInfo type.
  *
  * @param[out] os                Output stream.