COMPMID-754: Add validation to kernels.

Adds validation method to:
- CLConvolutionLayer

Change-Id: I95516e20cfb71c1e603c60fc6491ac695883a856
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/117355
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Jenkins <bsgcomp@arm.com>

5 files changed, 57 insertions, 7 deletions

diff --git a/arm_compute/core/CL/kernels/CLCol2ImKernel.h b/arm_compute/core/CL/kernels/CLCol2ImKernel.h
index bd86da1b5e..24d0fdd914 100644
--- a/arm_compute/core/CL/kernels/CLCol2ImKernel.h
+++ b/arm_compute/core/CL/kernels/CLCol2ImKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -72,6 +72,16 @@ public:
      * @param[in]  convolved_dims Output convolved dimensions.
      */
     void configure(const ICLTensor *input, ICLTensor *output, std::pair<unsigned int, unsigned int> convolved_dims);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLCol2ImKernel
+     *
+     * @param[in] input          The input tensor to convert. Data types supported: QS8/QS16/QASYMM8/F16/F32
+     * @param[in] output         The output tensor. 3 lower dimensions represent a single output [width, height, OFM],
+     *                           while the rest represent batch of outputs. Data types supported: Same as @p input
+     * @param[in] convolved_dims Output convolved dimensions.
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, std::pair<unsigned int, unsigned int> convolved_dims);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/CL/kernels/CLGEMMMatrixAdditionKernel.h b/arm_compute/core/CL/kernels/CLGEMMMatrixAdditionKernel.h
index 8f73d8c2c3..dc84a40ca8 100644
--- a/arm_compute/core/CL/kernels/CLGEMMMatrixAdditionKernel.h
+++ b/arm_compute/core/CL/kernels/CLGEMMMatrixAdditionKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -57,6 +57,15 @@ public:
      * @param[in]      beta   Weight of matrix C
      */
     void configure(const ICLTensor *input, ICLTensor *output, float beta);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLGEMMMatrixAdditionKernel.
+     *
+     * @param[in] input  Input tensor (Matrix C). Data types supported: QS8/QS16/F16/F32
+     * @param[in] output Output tensor. If this kernel is used to finalize the GEMM result (alpha * AB + beta * C), output must contain the result obtained by @ref CLGEMMMatrixMultiplyKernel. Data type supported: same as @p input
+     * @param[in] beta   Weight of matrix C
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *output, const float beta);
 
     // 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 e38e7e8a49..1ad302eedb 100644
--- a/arm_compute/core/CL/kernels/CLIm2ColKernel.h
+++ b/arm_compute/core/CL/kernels/CLIm2ColKernel.h
@@ -77,9 +77,6 @@ public:
      * @param[in]  has_bias    In case biases are provided expands the matrix with 1.
      */
     void configure(const ICLTensor *input, ICLTensor *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
-
-    // 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],
@@ -94,6 +91,9 @@ public:
      */
     static Status validate(const ITensorInfo *input, const ITensorInfo *output, const Size2D &kernel_dims, const PadStrideInfo &conv_info, bool has_bias);
 
+    // Inherited methods overridden:
+    void run(const Window &window, cl::CommandQueue &queue) override;
+
 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)
      *
diff --git a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
index 6c84ded49e..b9ede12e3d 100644
--- a/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
+++ b/arm_compute/core/CL/kernels/CLWeightsReshapeKernel.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017 ARM Limited.
+ * Copyright (c) 2017-2018 ARM Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -43,7 +43,6 @@ public:
     CLWeightsReshapeKernel &operator=(CLWeightsReshapeKernel &&) = default;
     /** Default destructor */
     ~CLWeightsReshapeKernel() = default;
-
     /** Set the input and output of the kernel.
      *
      * @param[in]  input  The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
@@ -54,6 +53,18 @@ public:
      * @param[out] output The output tensor. Should be a 2D Tensor. Data types supported: Same as @p input
      */
     void configure(const ICLTensor *input, const ICLTensor *biases, ICLTensor *output);
+    /** Static function to check if given info will lead to a valid configuration of @ref CLWeightsReshapeKernel
+     *
+     * @param[in] input  The input tensor to convert. Weights are 4D tensor with dimensions [kernel_x, kernel_y, IFM, OFM] if shared,
+     *                   and 5D tensor with dimensions [kernel_x, kernel_y, IFM, OFM,  num_patches] if unshared. Data types supported: QS8/QS16/QASYMM8/F16/F32
+     * @param[in] biases The shared biases tensor to append.  Bias is 1D tensor with dimensions [OFM] if shared and 2D tensor with
+     *                   dimensions [OFM, num_patches] if unshared. Data types supported: Same as @p input
+     *                   @warning Appending biases to weights reshaped matrix is not supported for quantized asymmetric types.
+     * @param[in] output The output tensor. Should be a 2D Tensor. Data types supported: Same as @p input
+     *
+     * @return a status
+     */
+    static Status validate(const ITensorInfo *input, const ITensorInfo *biases, const ITensorInfo *output);
 
     // Inherited methods overridden:
     void run(const Window &window, cl::CommandQueue &queue) override;
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index e51c6bbe98..c53ac4c71f 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -40,6 +40,17 @@ inline TensorShape compute_permutation_output_shape(const ITensorInfo &input, co
     permute(output_shape, perm);
     return output_shape;
 }
+inline TensorShape compute_weights_reshaped_shape(const ITensorInfo &weights, bool has_bias = false)
+{
+    // Calculate output shape
+    TensorShape weights_reshaped{ weights.tensor_shape() };
+    weights_reshaped.collapse(3);
+    const size_t tmp_dim = weights_reshaped[0];
+    weights_reshaped.set(0, weights_reshaped[1]);
+    weights_reshaped.set(1, tmp_dim + (has_bias ? 1 : 0));
+
+    return weights_reshaped;
+}
 inline TensorShape compute_interleaved_shape(const ITensorInfo &a, int mult_interleave4x4_height = 1)
 {
     // The interleaved output matrix will have the following shape: [ a_height * W, ceil(a_width / W) ] where W = 4 * mult_interleave4x4_height
@@ -101,6 +112,15 @@ inline TensorShape compute_im2col_shape(const ITensorInfo &input)
 
     return shape_im2col;
 }
+inline TensorShape compute_col2im_shape(const ITensorInfo &input, std::pair<unsigned int, unsigned int> convolved_dims)
+{
+    TensorShape col2im_shape{ input.tensor_shape() };
+    col2im_shape.set(0, convolved_dims.first);
+    col2im_shape.set(1, convolved_dims.second);
+    col2im_shape.set(2, input.tensor_shape()[0]);
+
+    return col2im_shape;
+}
 inline TensorShape compute_transposed_shape(const ITensorInfo &input)
 {
     TensorShape shape_transposed{ input.tensor_shape() };