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-rw-r--r--arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h12
-rw-r--r--arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h36
2 files changed, 41 insertions, 7 deletions
diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
index 784637a796..78f12daf9c 100644
--- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -126,12 +126,12 @@ public:
NEFullyConnectedLayer &operator=(NEFullyConnectedLayer &&) = default;
/** Set the input and output tensors.
*
- * @param[in] input Source tensor. Data type supported: QASYMM8/F16/F32.
+ * @param[in] input Source tensor. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor. The weights must be 2 dimensional.
* If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
* If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
* Data type supported: Same as @p input.
- * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8.
+ * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
* @param[out] output Destination tensor. Its shape should be equal to the output of a matrix multiplication between:
* - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
* - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
@@ -142,12 +142,12 @@ public:
FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
/** Static function to check if given info will lead to a valid configuration of @ref NEFullyConnectedLayer
*
- * @param[in] input Source tensor info. Data type supported: QASYMM8/F16/F32.
+ * @param[in] input Source tensor info. Data type supported: QASYMM8/QASYMM8_SIGNED/F16/F32.
* @param[in] weights Weights tensor info. The weights must be 2 dimensional.
* If this function is called after a Convolution Layer, the (transposed) weights will have as many rows as the product of the first 3 input's dimensions.
* If it is called after another FullyConnected Layer, the (transposed) weights will have as many rows as the input's first dimension.
* Data type supported: Same as @p input.
- * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8.
+ * @param[in] biases Bias tensor. Can be nullptr. Data type supported: Same as @p weights, S32 if @p weights is QASYMM8/QASYMM8_SIGNED.
* @param[in] output Destination tensor info. Its shape should be equal to the output of a matrix multiplication between:
* - The output of im2col on the input and the (transposed) 2D weights, if the function is called after a Convolution Layer
* - The input tensor and the (transposed) 2D weights, if the function is called after another FullyConnected Layer.
@@ -177,7 +177,7 @@ private:
weights_transformations::NEFullyConnectedLayerReshapeWeightsManaged _reshape_weights_managed_function;
NEGEMM _mm_gemm;
NEGEMMLowpMatrixMultiplyCore _mm_gemmlowp;
- NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPoint _gemmlowp_output_stage;
+ NEGEMMLowpOutputStage _gemmlowp_output_stage;
NEGEMMMatrixAccumulateBiasesKernel _accumulate_biases_kernel;
Tensor _flatten_output;
Tensor _gemmlowp_output;
diff --git a/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h b/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h
index b483d03c85..ca2cbbc268 100644
--- a/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h
+++ b/arm_compute/runtime/NEON/functions/NEGEMMLowpOutputStage.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2017-2019 ARM Limited.
+ * Copyright (c) 2017-2020 ARM Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -264,5 +264,39 @@ public:
*/
static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, int min = 0, int max = 0);
};
+
+/** Basic function to execute GEMMLowpQuantizeDown kernels on NEON.
+ *
+ * This function calls the following NEON kernels:
+ *
+ * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel
+ * -# @ref NEGEMMLowpQuantizeDownInt32ToUint8ScaleByFixedPointKernel
+ * -# @ref NEGEMMLowpQuantizeDownInt32ToInt8ScaleByFixedPointKernel
+ * -# @ref NEGEMMLowpQuantizeDownInt32ToInt16ScaleByFixedPointKernel
+*/
+class NEGEMMLowpOutputStage : public INESimpleFunctionNoBorder
+{
+public:
+ /** Initialise the kernel's inputs, output
+ *
+ * @param[in] input Input tensor. Data type supported: S32
+ * @param[in] bias Biases tensor. Only shared biases supported and it can be a nullptr if the biases addition is not required.
+ * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+ * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM16
+ * @param[in] info GEMMLowp output stage metadata.
+ */
+ void configure(const ITensor *input, const ITensor *bias, ITensor *output, const GEMMLowpOutputStageInfo &info);
+ /** Static function to check if given info will lead to a valid configuration of @ref NEGEMMLowpOutputStage
+ *
+ * @param[in] input Input tensor info. It is the output of @ref NEGEMMLowpMatrixMultiplyCore function. Data type supported: S32
+ * @param[in] bias Biases tensor info. Only shared biases supported and it can be a nullptr if the addition of biases is not required.
+ * Biases are 1D tensor with dimensions [OFM]. Data type supported: Same as @p input.
+ * @param[in] output Output tensor info. Data type supported: Data type supported: QASYMM8/QASYMM8_SIGNED/QSYMM16
+ * @param[in] info GEMMLowp output stage metadata.
+ *
+ * @return a status
+ */
+ static Status validate(const ITensorInfo *input, const ITensorInfo *bias, const ITensorInfo *output, const GEMMLowpOutputStageInfo &info);
+};
} // namespace arm_compute
#endif /*ARM_COMPUTE_NEGEMMLOWPOUTPUTSTAGE_H */