COMPMID-2111: ConcatenateLayer API should accept an index instead of an enum
Alters the concatenate layer to be layout agnostic and accept an index
as thec concatenation axis instead of an typed layout dependent
enumeration.
Change-Id: I0eaaf919f66a1ba1b09bbfb47c171fc1d4045530
Signed-off-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-on: https://review.mlplatform.org/c/994
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
diff --git a/arm_compute/graph/LayerDescriptors.h b/arm_compute/graph/LayerDescriptors.h
index 7909932..f52beab 100644
--- a/arm_compute/graph/LayerDescriptors.h
+++ b/arm_compute/graph/LayerDescriptors.h
@@ -32,7 +32,7 @@
{
namespace descriptors
{
-/** Common node parameters */
+/** Concatenate layer descriptor */
struct ConcatLayerDescriptor
{
/** Default constructor */
diff --git a/arm_compute/graph/Utils.h b/arm_compute/graph/Utils.h
index 4ffccec..2fa2f3b 100644
--- a/arm_compute/graph/Utils.h
+++ b/arm_compute/graph/Utils.h
@@ -110,12 +110,12 @@
size_t get_dimension_size(const TensorDescriptor &descriptor, const DataLayoutDimension data_layout_dimension);
/** Get index of a tensor's given dimension depending on its layout
*
- * @param[in] descriptor Descriptor
+ * @param[in] data_layout Data layout of the tensor
* @param[in] data_layout_dimension Tensor data layout dimension
*
* @return Idx of given dimension
*/
-size_t get_dimension_idx(const TensorDescriptor &descriptor, const DataLayoutDimension data_layout_dimension);
+size_t get_dimension_idx(DataLayout data_layout, const DataLayoutDimension data_layout_dimension);
/** Get the list of driving nodes of a given node
*
* @param[in] node Node to find the driving node of
diff --git a/arm_compute/graph/backends/FunctionHelpers.h b/arm_compute/graph/backends/FunctionHelpers.h
index e05f4bc..f6e6286 100644
--- a/arm_compute/graph/backends/FunctionHelpers.h
+++ b/arm_compute/graph/backends/FunctionHelpers.h
@@ -28,6 +28,7 @@
#include "arm_compute/graph/Tensor.h"
#include "arm_compute/graph/TypePrinter.h"
#include "arm_compute/graph/Types.h"
+#include "arm_compute/graph/Utils.h"
#include "arm_compute/graph/backends/FusedConvolutionBatchNormalizationFunction.h"
#include "arm_compute/graph/backends/Utils.h"
#include "arm_compute/graph/nodes/Nodes.h"
@@ -321,7 +322,8 @@
inputs.push_back(get_backing_tensor<TargetInfo>(node.input(i)));
}
typename TargetInfo::TensorType *output = get_backing_tensor<TargetInfo>(node.output(0));
- const DataLayoutDimension concat_axis = node.concatenation_axis();
+ const DataLayout data_layout = node.output(0) != nullptr ? node.output(0)->desc().layout : DataLayout::UNKNOWN;
+ const size_t concat_axis = get_dimension_idx(data_layout, node.concatenation_axis());
// Create and configure function
auto func = support::cpp14::make_unique<ConcatenateLayerFunction>();
diff --git a/arm_compute/runtime/CL/functions/CLConcatenateLayer.h b/arm_compute/runtime/CL/functions/CLConcatenateLayer.h
index 5cf09c8..d85a445 100644
--- a/arm_compute/runtime/CL/functions/CLConcatenateLayer.h
+++ b/arm_compute/runtime/CL/functions/CLConcatenateLayer.h
@@ -59,7 +59,7 @@
* @param[out] output Output tensor. Data types supported: Same as @p input.
* @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0, 1 and 2.
*/
- void configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, DataLayoutDimension axis);
+ void configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, size_t axis);
/** Static function to check if given info will lead to a valid configuration of @ref CLConcatenateLayer
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
@@ -71,7 +71,7 @@
*
* @return a status
*/
- static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis);
+ static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis);
// Inherited methods overridden:
void run() override;
@@ -81,5 +81,5 @@
unsigned int _num_inputs;
unsigned int _axis;
};
-}
+} // namespace arm_compute
#endif /* __ARM_COMPUTE_CLCONCATENATELAYER_H__ */
diff --git a/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h b/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
index 7dfbcf9..f8cda32 100644
--- a/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEConcatenateLayer.h
@@ -59,7 +59,7 @@
* @param[out] output Output tensor. Data types supported: Same as @p input.
* @param[in] axis Concatenation axis. Supported underlying concatenation axis are 0, 1 and 2.
*/
- void configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis);
+ void configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, size_t axis);
/** Static function to check if given info will lead to a valid configuration of @ref NEConcatenateLayer
*
* @note Input and output tensor dimensions preconditions defer depending on the concatenation axis.
@@ -71,7 +71,7 @@
*
* @return a status
*/
- static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis);
+ static Status validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis);
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h b/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h
index da38151..e2f2c4c 100644
--- a/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEDepthConcatenateLayer.h
@@ -89,5 +89,5 @@
std::unique_ptr<NEFillBorderKernel[]> _border_handlers_vector;
unsigned int _num_inputs;
};
-}
+} // namespace arm_compute
#endif /* __ARM_COMPUTE_NEDEPTHCONCATENATE_H__ */
diff --git a/src/graph/GraphBuilder.cpp b/src/graph/GraphBuilder.cpp
index b96a242..9f8dd69 100644
--- a/src/graph/GraphBuilder.cpp
+++ b/src/graph/GraphBuilder.cpp
@@ -221,14 +221,15 @@
// Get input tensor descriptor
const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
+ const DataLayout input_data_layout = input_tensor_desc.layout;
// Create weights node
TensorDescriptor w_desc = input_tensor_desc;
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::CHANNEL),
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::CHANNEL),
get_dimension_size(input_tensor_desc, DataLayoutDimension::CHANNEL) / num_groups);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::BATCHES), depth);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::BATCHES), depth);
if(!weights_quant_info.empty())
{
w_desc.quant_info = weights_quant_info;
@@ -275,14 +276,15 @@
// Get input tensor descriptor
const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
+ const DataLayout input_data_layout = input_tensor_desc.layout;
// Create weights node
TensorDescriptor w_desc = input_tensor_desc;
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::CHANNEL),
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::CHANNEL),
get_dimension_size(input_tensor_desc, DataLayoutDimension::CHANNEL));
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::BATCHES), depth);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::BATCHES), depth);
NodeID w_nid = add_const_node_with_name(g, params, "Weights", w_desc, std::move(weights_accessor));
@@ -328,12 +330,13 @@
// Get input tensor descriptor
const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
+ const DataLayout input_data_layout = input_tensor_desc.layout;
// Create weights node
TensorDescriptor w_desc = input_tensor_desc;
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
- w_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::CHANNEL),
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::WIDTH), kernel_spatial_extend.width);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::HEIGHT), kernel_spatial_extend.height);
+ w_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::CHANNEL),
get_dimension_size(input_tensor_desc, DataLayoutDimension::CHANNEL) * depth_multiplier);
if(!quant_info.empty())
{
@@ -595,13 +598,14 @@
// Get input tensor descriptor
const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
+ const DataLayout input_data_layout = input_tensor_desc.layout;
// Create mul node
TensorDescriptor mul_desc = input_tensor_desc;
- const size_t C = input_tensor_desc.shape[get_dimension_idx(mul_desc, DataLayoutDimension::CHANNEL)];
- mul_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::WIDTH), 1);
- mul_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::HEIGHT), 1);
- mul_desc.shape.set(get_dimension_idx(input_tensor_desc, DataLayoutDimension::CHANNEL), C);
+ const size_t C = input_tensor_desc.shape[get_dimension_idx(input_data_layout, DataLayoutDimension::CHANNEL)];
+ mul_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::WIDTH), 1);
+ mul_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::HEIGHT), 1);
+ mul_desc.shape.set(get_dimension_idx(input_data_layout, DataLayoutDimension::CHANNEL), C);
NodeID mul_const_nid = add_const_node_with_name(g, params, "Mul", mul_desc, std::move(mul_accessor));
NodeIdxPair mul_const_nidxp = { mul_const_nid, 0 };
diff --git a/src/graph/Utils.cpp b/src/graph/Utils.cpp
index 71a6fc5..4c34dd8 100644
--- a/src/graph/Utils.cpp
+++ b/src/graph/Utils.cpp
@@ -119,12 +119,12 @@
size_t get_dimension_size(const TensorDescriptor &descriptor, const DataLayoutDimension data_layout_dimension)
{
ARM_COMPUTE_ERROR_ON_MSG(descriptor.layout == DataLayout::UNKNOWN, "Cannot retrieve the dimension index for an unknown layout!");
- return descriptor.shape[get_dimension_idx(descriptor, data_layout_dimension)];
+ return descriptor.shape[get_dimension_idx(descriptor.layout, data_layout_dimension)];
}
-size_t get_dimension_idx(const TensorDescriptor &descriptor, const DataLayoutDimension data_layout_dimension)
+size_t get_dimension_idx(DataLayout data_layout, const DataLayoutDimension data_layout_dimension)
{
- ARM_COMPUTE_ERROR_ON_MSG(descriptor.layout == DataLayout::UNKNOWN, "Cannot retrieve the dimension index for an unknown layout!");
+ ARM_COMPUTE_ERROR_ON_MSG(data_layout == DataLayout::UNKNOWN, "Cannot retrieve the dimension index for an unknown layout!");
/* Return the index based on the data layout
* [N C H W]
@@ -134,13 +134,13 @@
switch(data_layout_dimension)
{
case DataLayoutDimension::CHANNEL:
- return (descriptor.layout == DataLayout::NCHW) ? 2 : 0;
+ return (data_layout == DataLayout::NCHW) ? 2 : 0;
break;
case DataLayoutDimension::HEIGHT:
- return (descriptor.layout == DataLayout::NCHW) ? 1 : 2;
+ return (data_layout == DataLayout::NCHW) ? 1 : 2;
break;
case DataLayoutDimension::WIDTH:
- return (descriptor.layout == DataLayout::NCHW) ? 0 : 1;
+ return (data_layout == DataLayout::NCHW) ? 0 : 1;
break;
case DataLayoutDimension::BATCHES:
return 3;
diff --git a/src/graph/mutators/DepthConcatSubTensorMutator.cpp b/src/graph/mutators/DepthConcatSubTensorMutator.cpp
index 0e0a26b..7994541 100644
--- a/src/graph/mutators/DepthConcatSubTensorMutator.cpp
+++ b/src/graph/mutators/DepthConcatSubTensorMutator.cpp
@@ -62,9 +62,9 @@
// Get output tensor
auto output_tensor = node->output(0);
- // Check concatenation axis (Sub-tensor optimization is support for concatenation axis >=2)
+ // Check concatenation axis (Sub-tensor optimization is supported for concatenation axis >=2)
auto *concat_node = arm_compute::utils::cast::polymorphic_downcast<ConcatenateLayerNode *>(node);
- if(output_tensor == nullptr || get_dimension_idx(output_tensor->desc(), concat_node->concatenation_axis()) < 2)
+ if(output_tensor == nullptr || get_dimension_idx(output_tensor->desc().layout, concat_node->concatenation_axis()) < 2)
{
continue;
}
diff --git a/src/graph/mutators/GroupedConvolutionMutator.cpp b/src/graph/mutators/GroupedConvolutionMutator.cpp
index d69d2cd..3d53f49 100644
--- a/src/graph/mutators/GroupedConvolutionMutator.cpp
+++ b/src/graph/mutators/GroupedConvolutionMutator.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -47,12 +47,12 @@
// Split input
const TensorDescriptor input_tensor_desc = get_tensor_descriptor(g, g.node(input.node_id)->outputs()[0]);
- const unsigned int input_idx = get_dimension_idx(input_tensor_desc, DataLayoutDimension::CHANNEL);
+ const unsigned int input_idx = get_dimension_idx(input_tensor_desc.layout, DataLayoutDimension::CHANNEL);
NodeID input_split = GraphBuilder::add_split_node(g, params, input, num_groups, input_idx);
// Split weights
const TensorDescriptor weights_tensor_desc = get_tensor_descriptor(g, g.node(weights)->outputs()[0]);
- const unsigned int batch_idx = get_dimension_idx(weights_tensor_desc, DataLayoutDimension::BATCHES);
+ const unsigned int batch_idx = get_dimension_idx(weights_tensor_desc.layout, DataLayoutDimension::BATCHES);
NodeID weights_split = GraphBuilder::add_split_node(g, params, { weights, 0 }, num_groups, batch_idx);
// Split bias
diff --git a/src/graph/nodes/ConcatenateLayerNode.cpp b/src/graph/nodes/ConcatenateLayerNode.cpp
index bbdc4dc..48da8b6 100644
--- a/src/graph/nodes/ConcatenateLayerNode.cpp
+++ b/src/graph/nodes/ConcatenateLayerNode.cpp
@@ -67,7 +67,7 @@
ARM_COMPUTE_ERROR_ON(input_descriptors.size() == 0);
TensorDescriptor output_descriptor = input_descriptors[0];
- const int axis_idx = get_dimension_idx(output_descriptor, axis);
+ const int axis_idx = get_dimension_idx(output_descriptor.layout, axis);
// Extract shapes
std::vector<const TensorShape *> shapes;
diff --git a/src/graph/nodes/ConvolutionLayerNode.cpp b/src/graph/nodes/ConvolutionLayerNode.cpp
index 15c7ff6..1c8dcae 100644
--- a/src/graph/nodes/ConvolutionLayerNode.cpp
+++ b/src/graph/nodes/ConvolutionLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -97,10 +97,11 @@
std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), output_width);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), output_height);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
return output_descriptor;
}
diff --git a/src/graph/nodes/DeconvolutionLayerNode.cpp b/src/graph/nodes/DeconvolutionLayerNode.cpp
index e7ccffd..b1a6db7 100644
--- a/src/graph/nodes/DeconvolutionLayerNode.cpp
+++ b/src/graph/nodes/DeconvolutionLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -66,10 +66,11 @@
info.pad().first, info.pad().second,
info.stride().first, info.stride().second);
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), output_width);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), output_height);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
return output_descriptor;
}
diff --git a/src/graph/nodes/DepthwiseConvolutionLayerNode.cpp b/src/graph/nodes/DepthwiseConvolutionLayerNode.cpp
index 935902d..cdd9e7b 100644
--- a/src/graph/nodes/DepthwiseConvolutionLayerNode.cpp
+++ b/src/graph/nodes/DepthwiseConvolutionLayerNode.cpp
@@ -86,10 +86,11 @@
std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), output_width);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), output_height);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::CHANNEL), input_channels * depth_multiplier);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), input_channels * depth_multiplier);
return output_descriptor;
}
diff --git a/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp
index 27a348f..c304a6c 100644
--- a/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp
+++ b/src/graph/nodes/FusedConvolutionBatchNormalizationNode.cpp
@@ -102,10 +102,11 @@
std::tie(output_width, output_height) = scaled_dimensions(input_width, input_height, kernel_width, kernel_height, info);
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), output_width);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), output_height);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), output_width);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), output_height);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), weights_descriptor.shape[3]);
return output_descriptor;
}
diff --git a/src/graph/nodes/PoolingLayerNode.cpp b/src/graph/nodes/PoolingLayerNode.cpp
index 26c145a..48b93c9 100644
--- a/src/graph/nodes/PoolingLayerNode.cpp
+++ b/src/graph/nodes/PoolingLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -57,9 +57,10 @@
std::tie(pooled_width, pooled_height) = scaled_dimensions(input_width, input_height, pool_size_x, pool_size_y, info.pad_stride_info());
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), pooled_width);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), pooled_height);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), pooled_width);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), pooled_height);
return output_descriptor;
}
diff --git a/src/graph/nodes/ReorgLayerNode.cpp b/src/graph/nodes/ReorgLayerNode.cpp
index 6b83f6b..21ad451 100644
--- a/src/graph/nodes/ReorgLayerNode.cpp
+++ b/src/graph/nodes/ReorgLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -53,10 +53,11 @@
ARM_COMPUTE_ERROR_ON_MSG((input_width % stride != 0), "The width of the input tensor must be a multiple of stride");
ARM_COMPUTE_ERROR_ON_MSG((input_height % stride != 0), "The height of the input tensor must be a multiple of stride");
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), input_width / stride);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), input_height / stride);
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::CHANNEL), input_channel * stride * stride);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), input_width / stride);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), input_height / stride);
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::CHANNEL), input_channel * stride * stride);
return output_descriptor;
}
diff --git a/src/graph/nodes/ResizeLayerNode.cpp b/src/graph/nodes/ResizeLayerNode.cpp
index a6aa7bf..a399229 100644
--- a/src/graph/nodes/ResizeLayerNode.cpp
+++ b/src/graph/nodes/ResizeLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -68,9 +68,10 @@
const Tensor *src = input(0);
ARM_COMPUTE_ERROR_ON(src == nullptr);
+ const DataLayout data_layout = src->desc().layout;
TensorDescriptor output_desc = src->desc();
- size_t width_idx = get_dimension_idx(output_desc, DataLayoutDimension::WIDTH);
- size_t height_idx = get_dimension_idx(output_desc, DataLayoutDimension::HEIGHT);
+ size_t width_idx = get_dimension_idx(data_layout, DataLayoutDimension::WIDTH);
+ size_t height_idx = get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT);
output_desc.shape.set(width_idx, static_cast<int>(output_desc.shape[width_idx] * _scale_width));
output_desc.shape.set(height_idx, static_cast<int>(output_desc.shape[height_idx] * _scale_height));
diff --git a/src/graph/nodes/UpsampleLayerNode.cpp b/src/graph/nodes/UpsampleLayerNode.cpp
index bdd39e8..88af122 100644
--- a/src/graph/nodes/UpsampleLayerNode.cpp
+++ b/src/graph/nodes/UpsampleLayerNode.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018 ARM Limited.
+ * Copyright (c) 2018-2019 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -54,9 +54,10 @@
const unsigned int input_width = get_dimension_size(input_descriptor, DataLayoutDimension::WIDTH);
const unsigned int input_height = get_dimension_size(input_descriptor, DataLayoutDimension::HEIGHT);
+ const DataLayout data_layout = input_descriptor.layout;
TensorDescriptor output_descriptor = input_descriptor;
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::WIDTH), input_width * info.x());
- output_descriptor.shape.set(get_dimension_idx(output_descriptor, DataLayoutDimension::HEIGHT), input_height * info.y());
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::WIDTH), input_width * info.x());
+ output_descriptor.shape.set(get_dimension_idx(data_layout, DataLayoutDimension::HEIGHT), input_height * info.y());
return output_descriptor;
}
diff --git a/src/runtime/CL/functions/CLConcatenateLayer.cpp b/src/runtime/CL/functions/CLConcatenateLayer.cpp
index 7edea3e..b9b3c5b 100644
--- a/src/runtime/CL/functions/CLConcatenateLayer.cpp
+++ b/src/runtime/CL/functions/CLConcatenateLayer.cpp
@@ -44,10 +44,10 @@
{
}
-void CLConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, DataLayoutDimension axis)
+void CLConcatenateLayer::configure(const std::vector<ICLTensor *> &inputs_vector, ICLTensor *output, size_t axis)
{
ARM_COMPUTE_ERROR_ON(output == nullptr);
- _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis);
+ _axis = axis;
_num_inputs = inputs_vector.size();
std::vector<ITensorInfo *> inputs_vector_info(inputs_vector.size());
@@ -135,30 +135,29 @@
}
}
-Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis)
+Status CLConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis)
{
ARM_COMPUTE_RETURN_ERROR_ON(output == nullptr);
const unsigned int num_inputs = inputs_vector.size();
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_RETURN_ERROR_ON(num_inputs < 2);
- const unsigned int _axis = get_data_layout_dimension_index(inputs_vector[0]->data_layout(), axis);
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->clone();
TensorShape output_shape{};
- if(_axis == Window::DimZ)
+ if(axis == Window::DimZ)
{
output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
}
else
{
- output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
+ output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
}
auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
unsigned int offset = 0;
- switch(_axis)
+ switch(axis)
{
case Window::DimX:
{
@@ -180,7 +179,7 @@
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
ARM_COMPUTE_RETURN_ON_ERROR(CLWidthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
- offset += input->dimension(_axis);
+ offset += input->dimension(axis);
}
break;
}
@@ -191,7 +190,7 @@
for(const auto &input : inputs_vector)
{
ARM_COMPUTE_RETURN_ON_ERROR(CLHeightConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
- offset += input->dimension(_axis);
+ offset += input->dimension(axis);
}
break;
}
@@ -200,7 +199,7 @@
for(const auto &input : inputs_vector)
{
ARM_COMPUTE_RETURN_ON_ERROR(CLDepthConcatenateLayerKernel::validate(input, offset, &tmp_output_info));
- offset += input->dimension(_axis);
+ offset += input->dimension(axis);
}
break;
}
diff --git a/src/runtime/CL/functions/CLPadLayer.cpp b/src/runtime/CL/functions/CLPadLayer.cpp
index f88cb38..dba7f23 100644
--- a/src/runtime/CL/functions/CLPadLayer.cpp
+++ b/src/runtime/CL/functions/CLPadLayer.cpp
@@ -141,7 +141,7 @@
}
// Concatenate the padding before and after with the input.
ICLTensor *out = (static_cast<int32_t>(i) == last_padding_dimension) ? output : &_concat_results[i];
- _concat_functions[i].configure(concat_vector, out, get_index_data_layout_dimension(prev->info()->data_layout(), i));
+ _concat_functions[i].configure(concat_vector, out, i);
prev = out;
}
}
diff --git a/src/runtime/NEON/functions/NEConcatenateLayer.cpp b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
index fa7b91c..e02c0c2 100644
--- a/src/runtime/NEON/functions/NEConcatenateLayer.cpp
+++ b/src/runtime/NEON/functions/NEConcatenateLayer.cpp
@@ -44,10 +44,10 @@
{
}
-void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, DataLayoutDimension axis)
+void NEConcatenateLayer::configure(const std::vector<ITensor *> &inputs_vector, ITensor *output, size_t axis)
{
ARM_COMPUTE_ERROR_ON(output == nullptr);
- _axis = get_data_layout_dimension_index(output->info()->data_layout(), axis);
+ _axis = axis;
_num_inputs = inputs_vector.size();
std::vector<ITensorInfo *> inputs_vector_info;
@@ -104,22 +104,21 @@
}
}
-Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, DataLayoutDimension axis)
+Status NEConcatenateLayer::validate(const std::vector<ITensorInfo *> &inputs_vector, const ITensorInfo *output, size_t axis)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(output);
ARM_COMPUTE_RETURN_ERROR_ON(inputs_vector.size() < 2);
- const unsigned int _axis = get_data_layout_dimension_index(inputs_vector[0]->data_layout(), axis);
// Output auto inizialitation if not yet initialized
TensorInfo tmp_output_info = *output->clone();
TensorShape output_shape{};
- if(_axis == Window::DimZ)
+ if(axis == Window::DimZ)
{
output_shape = arm_compute::misc::shape_calculator::calculate_depth_concatenate_shape(inputs_vector);
}
else
{
- output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, _axis);
+ output_shape = arm_compute::misc::shape_calculator::calculate_concatenate_shape(inputs_vector, axis);
}
auto_init_if_empty(tmp_output_info, output_shape, 1, inputs_vector[0]->data_type());
@@ -127,7 +126,7 @@
for(const auto &input : inputs_vector)
{
ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input);
- switch(_axis)
+ switch(axis)
{
case Window::DimX:
{
@@ -147,7 +146,7 @@
default:
ARM_COMPUTE_ERROR("Axis not supported");
}
- offset += input->dimension(_axis);
+ offset += input->dimension(axis);
}
return Status{};
diff --git a/src/runtime/NEON/functions/NEPadLayer.cpp b/src/runtime/NEON/functions/NEPadLayer.cpp
index 62a7d45..6af2ee8 100644
--- a/src/runtime/NEON/functions/NEPadLayer.cpp
+++ b/src/runtime/NEON/functions/NEPadLayer.cpp
@@ -182,7 +182,7 @@
}
// Concatenate the padding before and after with the input.
ITensor *out = (i == _num_dimensions - 1) ? output : &_concat_results[i];
- _concat_functions[i].configure(concat_vector, out, get_index_data_layout_dimension(input->info()->data_layout(), i));
+ _concat_functions[i].configure(concat_vector, out, i);
if(i != _num_dimensions - 1)
{
_concat_results[i].allocator()->allocate();
diff --git a/tests/validation/CL/DepthConcatenateLayer.cpp b/tests/validation/CL/DepthConcatenateLayer.cpp
index f4a693c..5da8a34 100644
--- a/tests/validation/CL/DepthConcatenateLayer.cpp
+++ b/tests/validation/CL/DepthConcatenateLayer.cpp
@@ -73,7 +73,7 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), DataLayoutDimension::CHANNEL));
+ bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), 2));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
@@ -95,7 +95,7 @@
// Create and configure function
CLConcatenateLayer concat_layer;
- concat_layer.configure({ &src1, &src2, &src3 }, &dst, DataLayoutDimension::CHANNEL);
+ concat_layer.configure({ &src1, &src2, &src3 }, &dst, 2);
}
template <typename T>
using CLDepthConcatenateLayerFixture = ConcatenateLayerValidationFixture<CLTensor, ICLTensor, CLAccessor, CLConcatenateLayer, T>;
diff --git a/tests/validation/CL/WidthConcatenateLayer.cpp b/tests/validation/CL/WidthConcatenateLayer.cpp
index 0ca6d72..2c1eb7f 100644
--- a/tests/validation/CL/WidthConcatenateLayer.cpp
+++ b/tests/validation/CL/WidthConcatenateLayer.cpp
@@ -77,7 +77,7 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw,&output_info.clone()->set_is_resizable(true),DataLayoutDimension::WIDTH ));
+ bool is_valid = bool(CLConcatenateLayer::validate(inputs_vector_info_raw,&output_info.clone()->set_is_resizable(true), 0));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
@@ -99,7 +99,7 @@
// Create and configure function
CLConcatenateLayer concat_layer;
- concat_layer.configure({ &src1, &src2, &src3 }, &dst, DataLayoutDimension::WIDTH);
+ concat_layer.configure({ &src1, &src2, &src3 }, &dst, 0);
}
template <typename T>
diff --git a/tests/validation/NEON/DepthConcatenateLayer.cpp b/tests/validation/NEON/DepthConcatenateLayer.cpp
index 1b355ae..0ddb220 100644
--- a/tests/validation/NEON/DepthConcatenateLayer.cpp
+++ b/tests/validation/NEON/DepthConcatenateLayer.cpp
@@ -55,13 +55,13 @@
TensorInfo(TensorShape(23U, 27U, 4U), 1, DataType::F32),
TensorInfo(TensorShape(16U, 27U, 6U), 1, DataType::F32)
})),
- framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(23U, 27U, 9U), 1, DataType::F16),
- TensorInfo(TensorShape(25U, 12U, 9U), 1, DataType::F32),
- TensorInfo(TensorShape(23U, 27U, 8U), 1, DataType::F32),
- TensorInfo(TensorShape(16U, 27U, 12U), 1, DataType::F32)
- })),
- framework::dataset::make("Expected", { false, false, false, true })),
- input_info1, input_info2, output_info,expected)
+ framework::dataset::make("OutputInfo", { TensorInfo(TensorShape(23U, 27U, 9U), 1, DataType::F16),
+ TensorInfo(TensorShape(25U, 12U, 9U), 1, DataType::F32),
+ TensorInfo(TensorShape(23U, 27U, 8U), 1, DataType::F32),
+ TensorInfo(TensorShape(16U, 27U, 12U), 1, DataType::F32)
+ })),
+ framework::dataset::make("Expected", { false, false, false, true })),
+ input_info1, input_info2, output_info,expected)
{
std::vector<TensorInfo> inputs_vector_info;
inputs_vector_info.emplace_back(std::move(input_info1));
@@ -73,7 +73,7 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), DataLayoutDimension::CHANNEL));
+ bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(false), 2));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
diff --git a/tests/validation/NEON/HeightConcatenateLayer.cpp b/tests/validation/NEON/HeightConcatenateLayer.cpp
index 0d08824..9c23fb9 100644
--- a/tests/validation/NEON/HeightConcatenateLayer.cpp
+++ b/tests/validation/NEON/HeightConcatenateLayer.cpp
@@ -77,7 +77,7 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(true), DataLayoutDimension::HEIGHT));
+ bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(true), 1));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
diff --git a/tests/validation/NEON/WidthConcatenateLayer.cpp b/tests/validation/NEON/WidthConcatenateLayer.cpp
index 20df3f4..ed840ef 100644
--- a/tests/validation/NEON/WidthConcatenateLayer.cpp
+++ b/tests/validation/NEON/WidthConcatenateLayer.cpp
@@ -75,8 +75,7 @@
inputs_vector_info_raw.emplace_back(&input);
}
- bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw,
- &output_info.clone()->set_is_resizable(true),DataLayoutDimension::WIDTH));
+ bool is_valid = bool(NEConcatenateLayer::validate(inputs_vector_info_raw, &output_info.clone()->set_is_resizable(true), 0));
ARM_COMPUTE_EXPECT(is_valid == expected, framework::LogLevel::ERRORS);
}
// clang-format on
diff --git a/tests/validation/fixtures/ConcatenateLayerFixture.h b/tests/validation/fixtures/ConcatenateLayerFixture.h
index db09957..39d4f9f 100644
--- a/tests/validation/fixtures/ConcatenateLayerFixture.h
+++ b/tests/validation/fixtures/ConcatenateLayerFixture.h
@@ -112,21 +112,7 @@
// Create and configure function
FunctionType concat;
- switch(axis)
- {
- case 0:
- concat.configure(src_ptrs, &dst, DataLayoutDimension::WIDTH);
- break;
- case 1:
- concat.configure(src_ptrs, &dst, DataLayoutDimension::HEIGHT);
- break;
- case 2:
- concat.configure(src_ptrs, &dst, DataLayoutDimension::CHANNEL);
- break;
- default:
- ARM_COMPUTE_ERROR("Not supported");
- break;
- }
+ concat.configure(src_ptrs, &dst, axis);
for(auto &src : srcs)
{