COMPMID-675 - Reworked NEGEMMLowp interface/function
The new interface makes NEGEMMLowp able to work with ASYMM8 data types.
Implemented 2 new functions:
- NEGEMMLowpMatrixMultiplyCore
- NEGEMMLowpOutputStage
These functions should make the integration in android NN doable
For more information about GEMMLowp:
https://github.com/google/gemmlowp/blob/master/doc/low-precision.md
Change-Id: Ie2c775f45234f68ca53dba644b3a912b997fd890
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/95504
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Pablo Tello <pablo.tello@arm.com>
diff --git a/arm_compute/core/NEON/NEKernels.h b/arm_compute/core/NEON/NEKernels.h
index 8dedf38..d78cec2 100644
--- a/arm_compute/core/NEON/NEKernels.h
+++ b/arm_compute/core/NEON/NEKernels.h
@@ -61,8 +61,9 @@
#include "arm_compute/core/NEON/kernels/NEGEMMAssemblyBaseKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMInterleave4x4Kernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMInterleaveBlockedKernel.h"
-#include "arm_compute/core/NEON/kernels/NEGEMMLowpFinalizeKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h"
+#include "arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.h"
+#include "arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMMatrixAccumulateBiasesKernel.h"
#include "arm_compute/core/NEON/kernels/NEGEMMMatrixAdditionKernel.h"
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpFinalizeKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpFinalizeKernel.h
deleted file mode 100644
index 8908fab..0000000
--- a/arm_compute/core/NEON/kernels/NEGEMMLowpFinalizeKernel.h
+++ /dev/null
@@ -1,103 +0,0 @@
-/*
- * Copyright (c) 2017 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_NEGEMMLOWPFINALIZEKERNEL_H__
-#define __ARM_COMPUTE_NEGEMMLOWPFINALIZEKERNEL_H__
-
-#include "arm_compute/core/NEON/INEKernel.h"
-
-namespace arm_compute
-{
-class ITensor;
-
-/* NEON kernel used to finalize the GEMMLowp result
- *
- * This kernel performs the following computations:
- *
- * -# Add offset terms to final result
- * -# Multiply each entry of result and round to nearest integer
- * -# Clamp the resulting int32 values to the [0..255] range and cast to uint8.
- */
-class NEGEMMLowpFinalizeKernel : public INEKernel
-{
-public:
- /** Constructor */
- NEGEMMLowpFinalizeKernel();
- /** Prevent instances of this class from being copied (As this class contains pointers)*/
- NEGEMMLowpFinalizeKernel(const NEGEMMLowpFinalizeKernel &) = delete;
- /** Prevent instances of this class from being copied (As this class contains pointers)*/
- NEGEMMLowpFinalizeKernel &operator=(const NEGEMMLowpFinalizeKernel &) = delete;
- /** Allow instances of this class to be moved */
- NEGEMMLowpFinalizeKernel(NEGEMMLowpFinalizeKernel &&) = default;
- /** Allow instances of this class to be moved */
- NEGEMMLowpFinalizeKernel &operator=(NEGEMMLowpFinalizeKernel &&) = default;
- /** Initialise the kernel's input and output.
- *
- * @note The input row-vectors @p vector_sum_col and @p vector_sum_row must be the output of @ref NEGEMMLowpMatrixBReductionKernel and @ref NEGEMMLowpMatrixAReductionKernel kernels.
- * These 2 vectors are needed to handle the offset of matrix product
- * https://github.com/google/gemmlowp/blob/master/doc/low-precision.md
- *
- * @param[in] vector_sum_col Input row-vector of sums of all the entries in each column of input1.
- * Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: S32
- * @param[in] vector_sum_row Input row-vector of sums of all the entries in each row of input0.
- * Note: vector_sum_row can be a nullptr in case b_offset = 0. Data type supported: same as @p vector_sum_col
- * @param[in] mm_result Input tensor containing the result of @ref NEGEMMLowpMatrixMultiplyKernel. Data type supported: same as @p vector_sum_col
- * @param[out] output Output tensor containing the result of GEMMLowP. Data type supported: S8
- * @param[in] num_mtx_a_cols Number of matrix A columns
- * @param[in] a_offset Offset to be added to each element of the matrix A.
- * @param[in] b_offset Offset to be added to each element of the matrix B.
- * @param[in] c_offset Offset to be added to each element of the output matrix
- * @param[in] c_mult_int Value to be multiplied to each entry of the result.
- * @param[in] shift Number of bits to shift right the result.
- */
- void configure(const ITensor *vector_sum_col, const ITensor *vector_sum_row, const ITensor *mm_result, ITensor *output, int32_t num_mtx_a_cols, int32_t a_offset, int32_t b_offset, int32_t c_offset,
- int32_t c_mult_int, int32_t shift);
-
- // Inherited methods overridden:
- void run(const Window &window, const ThreadInfo &info) override;
-
-private:
- /** Template function to run the finalize kernel
- *
- * @param[in] window Region on which to execute the kernel. (Must be a valid region of the window returned by window()).
- */
- template <bool add_a_offset, bool add_b_offset>
- void finalize(const Window &window);
- using FinalizeFunctionPtr = void (NEGEMMLowpFinalizeKernel::*)(const Window &window);
-
- FinalizeFunctionPtr _func;
- const ITensor *_vector_sum_col;
- const ITensor *_vector_sum_row;
- const ITensor *_mm_result;
- ITensor *_output;
- int32_t _a_offset;
- int32_t _b_offset;
- int32_t _c_offset;
- int32_t _k_offset;
- int32_t _c_mult_int;
- int32_t _shift;
- bool _slide_vector_sum_col;
-};
-} // namespace arm_compute
-
-#endif /* __ARM_COMPUTE_NEGEMMLOWPFINALIZEKERNEL_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h
index f145eb6..e9bfe4e 100644
--- a/arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h
+++ b/arm_compute/core/NEON/kernels/NEGEMMLowpMatrixMultiplyKernel.h
@@ -58,8 +58,8 @@
* The input matrices @p input0 and @p input1 must be the output of the kernels: @ref NEGEMMInterleave4x4Kernel and @ref NEGEMMTranspose1xWKernel. These two
* kernels change the layout of the original matrices to be more cache-friendly.
*
- * @param[in] input0 Input tensor containing the interleaved Matrix A. Data type supported: S8
- * @param[in] input1 Input tensor containing the transposed Matrix B. Data type supported: same as @p input0
+ * @param[in] input0 Input tensor containing the interleaved Matrix A. Data type supported: ASYMM8
+ * @param[in] input1 Input tensor containing the transposed1xW Matrix B. Data type supported: same as @p input0
* @param[out] output Output tensor to store the result of matrix multiplication. Data type supported: S32
*/
void configure(const ITensor *input0, const ITensor *input1, ITensor *output);
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.h
new file mode 100644
index 0000000..04b8433
--- /dev/null
+++ b/arm_compute/core/NEON/kernels/NEGEMMLowpOffsetContributionKernel.h
@@ -0,0 +1,79 @@
+/*
+ * Copyright (c) 2017 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_NEGEMMLOWPOFFSETCONTRIBUTIONKERNEL_H__
+#define __ARM_COMPUTE_NEGEMMLOWPOFFSETCONTRIBUTIONKERNEL_H__
+
+#include "arm_compute/core/NEON/INEKernel.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/* NEON kernel used to add the offset contribution after @ref NEGEMMLowpMatrixMultiplyKernel. The computation is performed in-place
+ *
+ * This kernel takes a final int32 accumulator value (the output of @NEGEMMLowpMatrixMultiplyKernel),
+ * and adds to it the offset contribution of matrix A and matrix B in-place.
+ *
+ */
+class NEGEMMLowpOffsetContributionKernel : public INEKernel
+{
+public:
+ /** Constructor */
+ NEGEMMLowpOffsetContributionKernel();
+ /** Prevent instances of this class from being copied (As this class contains pointers)*/
+ NEGEMMLowpOffsetContributionKernel(const NEGEMMLowpOffsetContributionKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers)*/
+ NEGEMMLowpOffsetContributionKernel &operator=(const NEGEMMLowpOffsetContributionKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ NEGEMMLowpOffsetContributionKernel(NEGEMMLowpOffsetContributionKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ NEGEMMLowpOffsetContributionKernel &operator=(NEGEMMLowpOffsetContributionKernel &&) = default;
+ /** Initialise the kernel's input and output.
+ *
+ * @param[in, out] mm_result Input tensor containing the result of @ref NEGEMMLowpMatrixMultiplyKernel. Data type supported: S32
+ * @param[in] vector_sum_col Input row-vector of sums of all the entries in each column of matrix B.
+ * Note: vector_sum_col can be a nullptr in case a_offset = 0. Data type supported: same as @p mm_result
+ * @param[in] vector_sum_row Input row-vector of sums of all the entries in each row of matrix A.
+ * Note: vector_sum_row can be a nullptr in case b_offset = 0. Data type supported: same as @p mm_result
+ * @param[in] k Number of matrix A columns or Matrix B rows
+ * @param[in] a_offset Offset to be added to each element of the matrix A.
+ * @param[in] b_offset Offset to be added to each element of the matrix B.
+ */
+ void configure(ITensor *mm_result, const ITensor *vector_sum_col, const ITensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset);
+
+ // Inherited methods overridden:
+ void run(const Window &window, const ThreadInfo &info) override;
+
+private:
+ const ITensor *_vector_sum_col;
+ const ITensor *_vector_sum_row;
+ ITensor *_mm_result;
+ int32_t _a_offset;
+ int32_t _b_offset;
+ int32_t _k_offset;
+ bool _slide_vector_sum_col;
+};
+} // namespace arm_compute
+
+#endif /* __ARM_COMPUTE_NEGEMMLOWPOFFSETCONTRIBUTIONKERNEL_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h
new file mode 100644
index 0000000..65f1042
--- /dev/null
+++ b/arm_compute/core/NEON/kernels/NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel.h
@@ -0,0 +1,78 @@
+/*
+ * Copyright (c) 2017 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_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALE_H__
+#define __ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALE_H__
+
+#include "arm_compute/core/NEON/INEKernel.h"
+
+namespace arm_compute
+{
+class ITensor;
+
+/* NEON kernel used to quantize down the int32 accumulator values of GEMMLowp to QASYMM8
+ *
+ * This kernel takes a final int32 accumulator value (the output of @ref NEGEMMLowpMatrixMultiplyKernel), and processes it to obtain the final QASYMM8 value.
+ * The following computations will be performed by the kernel:
+ *
+ * -# Add offset terms to final result
+ * -# Multiply each entry of result and round to nearest integer
+ * -# Clamp the resulting int32 values to the [0..255] range and cast to QASYMM8.
+ *
+ */
+class NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel : public INEKernel
+{
+public:
+ /** Constructor */
+ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel();
+ /** Prevent instances of this class from being copied (As this class contains pointers)*/
+ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &) = delete;
+ /** Prevent instances of this class from being copied (As this class contains pointers)*/
+ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(const NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &) = delete;
+ /** Allow instances of this class to be moved */
+ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel(NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = default;
+ /** Allow instances of this class to be moved */
+ NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &operator=(NEGEMMLowpQuantizeDownInt32ToUint8ScaleKernel &&) = default;
+ /** Initialise the kernel's input and output.
+ *
+ * @param[in] input Input tensor. Data type supported: S32
+ * @param[out] output Output tensor. Data type supported: Data type supported: QASYMM8
+ * @param[in] result_offset Offset to be added to each element of the input matrix
+ * @param[in] result_mult_int Value to be multiplied to each element of the input matrix when once the result_offset has been add
+ * @param[in] result_shift Number of bits to shift right the result before converting back to QASYMM8
+ */
+ void configure(const ITensor *input, ITensor *output, int result_offset, int result_mult_int, int result_shift);
+
+ // Inherited methods overridden:
+ void run(const Window &window, const ThreadInfo &info) override;
+
+private:
+ const ITensor *_input;
+ ITensor *_output;
+ int32_t _result_offset;
+ int32_t _result_mult_int;
+ int32_t _result_shift;
+};
+} // namespace arm_compute
+
+#endif /* __ARM_COMPUTE_NEGEMMLOWPQUANTIZEDOWNINT32TOUINT8SCALE_H__ */
diff --git a/arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h b/arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h
index a069969..6eee54a 100644
--- a/arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h
+++ b/arm_compute/core/NEON/kernels/NEGEMMLowpReductionKernel.h
@@ -45,10 +45,9 @@
/** Allow instances of this class to be moved */
INEGEMMLowpReductionKernel &operator=(INEGEMMLowpReductionKernel &&) = default;
-public:
/** Initialise the kernel's input and output.
*
- * @param[in] input Input tensor containing the interleaved or transposed matrix. Data type supported: S8
+ * @param[in] input Input tensor. Data type supported: S8
* @param[out] output Output row-vector of sums of all the entries in each row/col of input tensor. Data type supported: S32
* @param[in] k Number of matrix A columns (or matrix B rows)
* @param[in] is_reshaped True if the input tensor has been reshaped
@@ -72,14 +71,12 @@
public:
/** Initialise the kernel's input and output.
*
- * @note The input matrix @p mtx_a_interleaved4x4 must be the output of @ref NEGEMMInterleave4x4Kernel.
- *
- * @param[in] mtx_a_interleaved4x4 Input tensor containing the interleaved Matrix A. Data type supported: U8
- * @param[out] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a_interleaved4x4. Data type supported: S32
- * @param[in] num_mtx_a_cols Number of matrix A columns
- * @param[in] is_interleaved4x4 True if the input tensor is interleaved4x4
+ * @param[in] mtx_a Input tensor. Data type supported: QASYMM8
+ * @param[out] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32
+ * @param[in] num_mtx_a_cols Number of matrix A columns
+ * @param[in] is_interleaved4x4 True if the matrix A has been interleaved4x4
*/
- void configure(const ITensor *mtx_a_interleaved4x4, ITensor *vector_sum_row, int32_t num_mtx_a_cols, bool is_interleaved4x4) override;
+ void configure(const ITensor *mtx_a, ITensor *vector_sum_row, int32_t num_mtx_a_cols, bool is_interleaved4x4) override;
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;
@@ -95,14 +92,12 @@
public:
/** Initialise the kernel's input and output.
*
- * @note The input matrix @p mtx_b_transposed1xW must be the output of @ref NEGEMMTranspose1xWKernel kernel.
- *
- * @param[in] mtx_b_transposed1xW Input tensor containing the transposed Matrix B. Data type supported: Data type supported: U8
- * @param[out] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b_transposed1xW. Data type supported: S32
- * @param[in] num_mtx_b_rows Number of matrix B rows
- * @param[in] is_transposed1xW True if the input tensor is transposed 1xW
+ * @param[in] mtx_b Input tensor. Data type supported: Data type supported: QASYMM8
+ * @param[out] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
+ * @param[in] num_mtx_b_rows Number of matrix B rows
+ * @param[in] is_transposed1xW True if the input tensor is transposed 1xW
*/
- void configure(const ITensor *mtx_b_transposed1xW, ITensor *vector_sum_col, int32_t num_mtx_b_rows, bool is_transposed1xW) override;
+ void configure(const ITensor *mtx_b, ITensor *vector_sum_col, int32_t num_mtx_b_rows, bool is_transposed1xW) override;
// Inherited methods overridden:
void run(const Window &window, const ThreadInfo &info) override;