COMPMID-897 Merge batch normalization with bounded relu
Change-Id: I9a607fe620f795cdea1a99fdd3f5f8c2fc76f980
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/119234
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
diff --git a/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h b/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h
index 8643d83..fee5dd3 100644
--- a/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLBatchNormalizationLayerKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -52,35 +52,38 @@
*
* @note If the output tensor is a nullptr, the batch normalization function will be performed in-place
*
- * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
- * 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
- * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
+ * 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
- void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon);
+ void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon,
+ ActivationLayerInfo act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayerKernel
*
- * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result.
- * 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
- * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result.
+ * 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output,
const ITensorInfo *mean, const ITensorInfo *var,
const ITensorInfo *beta, const ITensorInfo *gamma,
- float epsilon);
+ float epsilon, ActivationLayerInfo act_info);
// Inherited methods overridden:
void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.h b/arm_compute/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.h
index 2bbd6a8..15d7f79 100644
--- a/arm_compute/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.h
+++ b/arm_compute/core/GLES_COMPUTE/kernels/GCBatchNormalizationLayerKernel.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -50,16 +50,18 @@
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: F16/F32.
- * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] input Source tensor. 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: F16/F32.
+ * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
- void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon);
+ void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon,
+ ActivationLayerInfo act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run(const Window &window) override;
diff --git a/arm_compute/core/Types.h b/arm_compute/core/Types.h
index 5a08ac9..3affe7e 100644
--- a/arm_compute/core/Types.h
+++ b/arm_compute/core/Types.h
@@ -713,6 +713,7 @@
LINEAR /**< Linear ( \f$ f(x)= ax + b \f$ ) */
};
+ ActivationLayerInfo() = default;
/** Default Constructor
*
* @param[in] f The activation function to use.
@@ -721,7 +722,7 @@
* @param[in] b (Optional) The beta parameter used by some activation functions (@ref ActivationFunction::LINEAR, @ref ActivationFunction::LU_BOUNDED_RELU, @ref ActivationFunction::TANH).
*/
ActivationLayerInfo(ActivationFunction f, float a = 0.0f, float b = 0.0f)
- : _act(f), _a(a), _b(b)
+ : _act(f), _a(a), _b(b), _enabled(true)
{
}
ActivationFunction activation() const
@@ -736,11 +737,16 @@
{
return _b;
}
+ bool enabled() const
+ {
+ return _enabled;
+ }
private:
- ActivationFunction _act;
- float _a;
- float _b;
+ ActivationFunction _act = { ActivationLayerInfo::ActivationFunction::LOGISTIC };
+ float _a = {};
+ float _b = {};
+ bool _enabled = { false };
};
/** Normalization Layer Information class */
diff --git a/arm_compute/graph/nodes/BatchNormalizationLayer.h b/arm_compute/graph/nodes/BatchNormalizationLayer.h
index df7b1d1..266c390 100644
--- a/arm_compute/graph/nodes/BatchNormalizationLayer.h
+++ b/arm_compute/graph/nodes/BatchNormalizationLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -40,15 +40,16 @@
public:
/** Default constructor
*
- * @param[in] mean Mean values tensor
- * @param[in] var Var values tensor
- * @param[in] gamma Gamma values tensor
- * @param[in] beta Beta values tensor
- * @param[in] epsilon Epsilon value
+ * @param[in] mean Mean values tensor
+ * @param[in] var Var values tensor
+ * @param[in] gamma Gamma values tensor
+ * @param[in] beta Beta values tensor
+ * @param[in] epsilon Epsilon value
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
template <typename AccessorType>
- BatchNormalizationLayer(AccessorType &&mean, AccessorType &&var, AccessorType &&gamma, AccessorType &&beta, float epsilon)
- : _mean(std::move(mean)), _var(std::move(var)), _gamma(std::move(gamma)), _beta(std::move(beta)), _epsilon(epsilon)
+ BatchNormalizationLayer(AccessorType &&mean, AccessorType &&var, AccessorType &&gamma, AccessorType &&beta, float epsilon, ActivationLayerInfo act_info = ActivationLayerInfo())
+ : _mean(std::move(mean)), _var(std::move(var)), _gamma(std::move(gamma)), _beta(std::move(beta)), _epsilon(epsilon), _act_info(act_info)
{
}
@@ -56,11 +57,12 @@
std::unique_ptr<arm_compute::IFunction> instantiate_node(GraphContext &ctx, ITensorObject *input, ITensorObject *output) override;
private:
- Tensor _mean;
- Tensor _var;
- Tensor _gamma;
- Tensor _beta;
- float _epsilon;
+ Tensor _mean;
+ Tensor _var;
+ Tensor _gamma;
+ Tensor _beta;
+ float _epsilon;
+ ActivationLayerInfo _act_info;
};
} // namespace graph
} // namespace arm_compute
diff --git a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h
index 127de10..3d5145a 100644
--- a/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h
+++ b/arm_compute/runtime/CL/functions/CLBatchNormalizationLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -48,35 +48,38 @@
*
* @note If the output tensor is a nullptr, the batch normalization function will be performed in-place
*
- * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
- * 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
- * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
+ * 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
- void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon);
+ void configure(ICLTensor *input, ICLTensor *output, const ICLTensor *mean, const ICLTensor *var, const ICLTensor *beta, const ICLTensor *gamma, float epsilon,
+ ActivationLayerInfo act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref CLBatchNormalizationLayer
*
- * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result.
- * 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
- * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] input Source tensor info. In case of @p output tensor info = nullptr, this tensor will store the result.
+ * 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output,
const ITensorInfo *mean, const ITensorInfo *var,
const ITensorInfo *beta, const ITensorInfo *gamma,
- float epsilon);
+ float epsilon, ActivationLayerInfo act_info);
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h b/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h
index 9d81b9a..01e53d2 100644
--- a/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h
+++ b/arm_compute/runtime/GLES_COMPUTE/functions/GCBatchNormalizationLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -46,16 +46,18 @@
GCBatchNormalizationLayer();
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: F16/F32.
- * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] input Source tensor. 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: F16/F32.
+ * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
- void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon);
+ void configure(const IGCTensor *input, IGCTensor *output, const IGCTensor *mean, const IGCTensor *var, const IGCTensor *beta, const IGCTensor *gamma, float epsilon,
+ ActivationLayerInfo act_info = ActivationLayerInfo());
// Inherited methods overridden:
void run() override;
diff --git a/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h b/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h
index 1933468..5c8200b 100644
--- a/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEBatchNormalizationLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -27,6 +27,7 @@
#include "arm_compute/core/NEON/kernels/NEBatchNormalizationLayerKernel.h"
#include "arm_compute/core/Types.h"
#include "arm_compute/runtime/IFunction.h"
+#include "arm_compute/runtime/NEON/functions/NEActivationLayer.h"
namespace arm_compute
{
@@ -47,41 +48,47 @@
*
* @note If the output tensor is a nullptr, the batch normalization function will be performed in-place
*
- * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
- * 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
- * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in, out] input Source tensor. In case of @p output tensor = nullptr, this tensor will store the result.
+ * 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * @param[out] output Destination tensor. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*/
- void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon);
+ void configure(ITensor *input, ITensor *output, const ITensor *mean, const ITensor *var, const ITensor *beta, const ITensor *gamma, float epsilon,
+ ActivationLayerInfo act_info = ActivationLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref NEBatchNormalizationLayer
*
- * @param[in] input Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result.
- * 3 lower dimensions represent a single input with dimensions [width, height, FM].
- * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
- * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
- * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
- * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] input Source tensor info. In case of @p output tensor = nullptr, this tensor will store the result.
+ * 3 lower dimensions represent a single input with dimensions [width, height, FM].
+ * The rest are optional and used for representing batches. Data types supported: QS8/QS16/F16/F32.
+ * @param[in] output Destination tensor info. Output will have the same number of dimensions as input. Data type supported: same as @p input
+ * @param[in] mean Mean values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] var Variance values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] beta Beta values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] gamma Gamma values tensor info. 1 dimension with size equal to the feature maps [FM]. Data types supported: Same as @p input
+ * @param[in] epsilon Small value to avoid division with zero.
+ * @param[in] act_info (Optional) Activation layer information in case of a fused activation. Only RELU, BOUNDED_RELU and LU_BOUNDED_RELU supported.
*
* @return a status
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *output,
const ITensorInfo *mean, const ITensorInfo *var,
const ITensorInfo *beta, const ITensorInfo *gamma,
- float epsilon);
+ float epsilon, ActivationLayerInfo act_info);
// Inherited methods overridden:
void run() override;
private:
NEBatchNormalizationLayerKernel _norm_kernel; /**< Batch normalization layer kernel */
+ // COMPMID-906 Use fused activation in NEON Batch normalization
+ NEActivationLayer _act_func;
+ bool _act_info_enabled;
};
}
#endif /* __ARM_COMPUTE_NEBATCHNORMALIZATIONLAYER_H__ */