COMPMID-617: Adds CLFullyConnectionLayer validation support

Change-Id: I4d2eb9872a3165fdcaa7784596e441cbe563dbc2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/112577
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Ioan-Cristian Szabo <ioan-cristian.szabo@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

8 files changed, 90 insertions, 1 deletions

diff --git a/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h b/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h
index c87fb2cd66..2520eff5de 100644
--- a/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMInterleave4x4Kernel.h
@@ -68,6 +68,14 @@ public:
      * @param[out] output Output tensor. Data type supported: same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMInterleave4x4Kernel
+     *
+     * @param[in] input  Input tensor info. Data types supported: U8/S8/QS8/QASYMM8/U16/S16/QS16/F16/U32/S32/F32
+     * @param[in] output Output tensor info which stores the interleaved matrix. Data type supported: same as @p input.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output);
 
     // Inherited methods overridden
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h
index b60b80618c..3ad3ced003 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.h
@@ -61,6 +61,16 @@ public:
      * @param[in]  is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMTranspose1xWKernel
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, bool is_interleaved_transposed = true);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixMultiplyKernel
+     *
+     * @param[in] input0                    Input tensor info containing the interleaved Matrix A. Data type supported: QASYMM8
+     * @param[in] input1                    Input tensor info containing the transposed Matrix B. Data type supported: same as @p input0
+     * @param[in] output                    Output tensor info to store the result of matrix multiplication. Data type supported: S32
+     * @param[in] is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMTranspose1xWKernel
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed = true);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h
index 5f2e025687..871b97c1d7 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpOffsetContributionKernel.h
@@ -68,6 +68,19 @@ public:
      * @param[in]      b_offset       Offset to be added to each element of the matrix B.
      */
     void configure(ICLTensor *mm_result, const ICLTensor *vector_sum_col, const ICLTensor *vector_sum_row, int32_t k, int32_t a_offset, int32_t b_offset);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpOffsetContributionKernel
+     *
+     * @param[in] mm_result      Input tensor containing the result of @ref CLGEMMLowpOffsetContributionKernel. 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] 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.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *mm_result, const ITensorInfo *vector_sum_col, const ITensorInfo *vector_sum_row, int32_t a_offset, int32_t b_offset);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h b/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h
index aa0583fe81..12c12ef99a 100644
--- a/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMLowpReductionKernel.h
@@ -71,6 +71,14 @@ public:
      * @param[out] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32
      */
     void configure(const ICLTensor *mtx_a, ICLTensor *vector_sum_row) override;
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixAReductionKernel
+     *
+     * @param[in] mtx_a          Input tensor. Data type supported: QASYMM8
+     * @param[in] vector_sum_row Output row-vector of sums of all the entries in each row of mtx_a. Data type supported: S32
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *mtx_a, const ITensorInfo *vector_sum_row);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
@@ -90,6 +98,14 @@ public:
      * @param[out] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
      */
     void configure(const ICLTensor *mtx_b, ICLTensor *vector_sum_col) override;
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMLowpMatrixBReductionKernel
+     *
+     * @param[in] mtx_b          Input tensor. Data type supported: Data type supported: QASYMM8
+     * @param[in] vector_sum_col Output row-vector of sums of all the entries in each column of mtx_b. Data type supported: S32
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *mtx_b, const ITensorInfo *vector_sum_col);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
index 9348ff8ca8..2956f93cdc 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixAccumulateBiasesKernel.h
@@ -50,6 +50,15 @@ public:
      * @param[in]      biases The shared biases tensor to append. It must be 1D tensor. Data types supported: Same as @p input
      */
     void configure(ICLTensor *accum, const ICLTensor *biases);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixAccumulateBiasesKernel
+     *
+     * @param[in] accum      The accumulate tensor to convert. Data types supported: QS8/QS16/F16/F32
+     * @param[in] biases     The shared biases tensor to append. It must be 1D tensor. Data types supported: Same as @p input
+     * @param[in] gpu_target GPU target
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *accum, const ITensorInfo *biases, GPUTarget gpu_target);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
index 5af9091416..4e73d7eb13 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixMultiplyKernel.h
@@ -60,6 +60,18 @@ public:
      * @param[in]  is_interleaved_transposed (Optional) True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMTranspose1xWKernel
      */
     void configure(const ICLTensor *input0, const ICLTensor *input1, ICLTensor *output, float alpha, bool is_interleaved_transposed = true);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixMultiplyKernel
+     *
+     * @param[in] input0                    Input tensor containing the Matrix A. Data types supported: QS8/QS16/F16/F32
+     * @param[in] input1                    Input tensor containing the Matrix B. Data type supported: same as @p input0
+     * @param[in] output                    Output tensor to store the result of matrix multiplication. Data type supported: same as @p input0
+     * @param[in] alpha                     Weight of the matrix product
+     * @param[in] is_interleaved_transposed True if input0 and input1 have been reshaped respectively using @ref CLGEMMInterleave4x4Kernel and @ref CLGEMMTranspose1xWKernel
+     * @param[in] gpu_target                GPU Target
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, float alpha, bool is_interleaved_transposed, GPUTarget gpu_target);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h b/arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h
index 8a37720462..8721643c1e 100644
--- a/arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMTranspose1xWKernel.h
@@ -74,6 +74,14 @@ public:
      * @param[out] output Output tensor. Data type supported: same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMTranspose1xWKernel
+     *
+     * @param[in] input  Input tensor. Data types supported: U8/S8/QS8/QASYMM8/U16/S16/QS16/F16/U32/S32/F32
+     * @param[in] output Output tensor. Data type supported: same as @p input.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLIm2ColKernel.h b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
index 1d8b5500c1..88de1ba002 100644
--- a/arm_compute/core/CL/kernels/CLIm2ColKernel.h
+++ b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
@@ -69,7 +69,7 @@ public:
     /** Set the input and output of the kernel.
      *
      * @param[in]  input       The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
-     *                         while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QS16/QASYMM8/F16/F32
+     *                         while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QASYMM8/QS16/F16/F32
      * @param[out] output      The output tensor. First 2 lower dimensions represent a transform of each 3D input,
      *                         while every dimension above represents a batch. Data types supported: Same as @p input
      * @param[in]  kernel_dims The kernel dimensions (width and height).
@@ -80,6 +80,19 @@ public:
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
+    /** Static function to check if given info will lead to a valid configuration of @ref CLIm2ColKernel
+     *
+     * @param[in] input       The input tensor to convert. 3 lower dimensions represent a single input [width, height, IFM],
+     *                        while every optional dimension from 4 and above represent a batch of inputs. Data types supported: QS8/QASYMM8/QS16/F16/F32
+     * @param[in] output      The output tensor. First 2 lower dimensions represent a transform of each 3D input,
+     *                        while every dimension above represents a batch. Data types supported: Same as @p input
+     * @param[in] kernel_dims The kernel dimensions (width and height).
+     * @param[in] conv_info   Contains padding and stride information described in @ref PadStrideInfo.
+     * @param[in] has_bias    In case biases are provided expands the matrix with 1.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
 
 private:
     /** Run the reshape kernel optimised for the special case (stride is 1, padding is 0 and kernel's low 3 dimensions are same as input)