[ONCPUML-968] Fixed format kernel support in additional APIs

Implements required plumbing in order to be able to ask and execute
fixed format kernels from NEFullyConnected, NEGEMM and NEGEMMConv2d.
These APIs are used to accelerate oneDNN primitives (inner product, matrix
multiplication and indirect GEMM respectively) and without changes it
would not be possible to call fixed format kernels from those oneDNN
primitives.

Change-Id: I27534f0491ce28d0ccb98c19f318bd33dcdf2ff5
Signed-off-by: Milos Puzovic <milos.puzovic@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/7999
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-by: Pablo Marquez Tello <pablo.tello@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 29 insertions, 13 deletions

diff --git a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
index aa96716d38..2b4f848b22 100644
--- a/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
+++ b/arm_compute/runtime/NEON/functions/NEFullyConnectedLayer.h
@@ -1,5 +1,5 @@
 /*
- * Copyright (c) 2017-2021 Arm Limited.
+ * Copyright (c) 2017-2022 Arm Limited.
  *
  * SPDX-License-Identifier: MIT
  *
@@ -112,20 +112,21 @@ public:
      * |QASYMM8        |QASYMM8            |S32    |QASYMM8        |
      * |QASYMM8_SIGNED |QASYMM8_SIGNED     |S32    |QASYMM8_SIGNED |
      *
-     * @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/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.
-     *                     Data type supported: Same as @p input.
-     * @param[in]  fc_info (Optional) Fully connected layer additional info
+     * @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/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.
+     *                          Data type supported: Same as @p input.
+     * @param[in]  fc_info      (Optional) Fully connected layer additional info
+     * @param[in]  weights_info (Optional) Stores neccessary compute information when weights are already reshaped
      */
     void configure(const ITensor *input, const ITensor *weights, const ITensor *biases, ITensor *output,
-                   FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
+                   FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo(), const WeightsInfo &weights_info = WeightsInfo());
     /** Static function to check if given info will lead to a valid configuration of @ref NEFullyConnectedLayer
      *
      * Similar to @ref NEFullyConnectedLayer
@@ -135,6 +136,21 @@ public:
     static Status validate(const ITensorInfo *input, const ITensorInfo *weights, const ITensorInfo *biases, const ITensorInfo *output,
                            FullyConnectedLayerInfo fc_info = FullyConnectedLayerInfo());
 
+    /** Static function that queries whether fixed-format kernel exists for a given problem description
+     *
+     * @param[out] expected_weight_format Format in which weights should be for found fixed format kernel
+     * @param[in]  input                  Source tensor
+     * @param[in]  weights                Weights tensor.
+     * @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
+     * @param[in]  fc_info                Fully connected layer additional info
+     * @param[in]  weights_info           Describes weights shape
+     *
+     * @return a status
+     */
+    static Status has_opt_impl(arm_compute::WeightFormat &expected_weight_format, const ITensorInfo *input, const ITensorInfo *weights,
+                               const ITensorInfo *biases, const ITensorInfo *output, const FullyConnectedLayerInfo &fc_info, const WeightsInfo &weights_info);
+
     //Inherited methods override
     void run() override;
     void prepare() override;