[ONCPUML-970] Fast math mode for fixed format kernels

Minor tweaks and test for running fixed format kernels with BF16
operations when specified by the user.

Change-Id: Ic8167f67b86b1298da65e46cfebed9f3b86940e4
Signed-off-by: Milos Puzovic <milos.puzovic@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/8000
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>

1 files changed, 18 insertions, 17 deletions

diff --git a/tests/validation/fixtures/ConvolutionLayerFixture.h b/tests/validation/fixtures/ConvolutionLayerFixture.h
index c58a0a2c91..63e6dc9377 100644
--- a/tests/validation/fixtures/ConvolutionLayerFixture.h
+++ b/tests/validation/fixtures/ConvolutionLayerFixture.h
@@ -122,14 +122,14 @@ protected:
         {
             case DataType::QASYMM8:
             {
-                std::pair<int, int> bounds = get_quantized_bounds(tensor.quantization_info(), -1.0f, 1.0f);
+                std::pair<int, int>                     bounds = get_quantized_bounds(tensor.quantization_info(), -1.0f, 1.0f);
                 std::uniform_int_distribution<uint32_t> distribution(bounds.first, bounds.second);
                 library->fill(tensor, distribution, i);
                 break;
             }
             case DataType::QASYMM8_SIGNED:
             {
-                std::pair<int, int> bounds = get_quantized_qasymm8_signed_bounds(tensor.quantization_info(), -1.0f, 1.0f);
+                std::pair<int, int>                    bounds = get_quantized_qasymm8_signed_bounds(tensor.quantization_info(), -1.0f, 1.0f);
                 std::uniform_int_distribution<int32_t> distribution(bounds.first, bounds.second);
                 library->fill(tensor, distribution, i);
                 break;
@@ -476,7 +476,7 @@ inline void rearrange_data(const AccessorType src, AccessorType dst, const arm_c
                 }
 }
 
-template <typename ConvolutionFunction, typename TensorClass, typename AccessorType, typename ScalarType>
+template <typename ConvolutionFunction, typename TensorClass, typename AccessorType, typename ScalarType, bool enable_fast_math>
 class VariableWeightsFixtureBaseClass : public framework::Fixture
 {
 public:
@@ -581,14 +581,14 @@ protected:
     SimpleTensor<ScalarType>             _reference{};
 };
 
-template <typename ConvolutionFunction, typename TensorClass, typename AccessorType, typename ScalarType>
-class VariableWeightsFixture : public VariableWeightsFixtureBaseClass<ConvolutionFunction, TensorClass, AccessorType, ScalarType>
+template <typename ConvolutionFunction, typename TensorClass, typename AccessorType, typename ScalarType, bool enable_fast_math>
+class VariableWeightsFixture : public VariableWeightsFixtureBaseClass<ConvolutionFunction, TensorClass, AccessorType, ScalarType, enable_fast_math>
 {
     void configure_and_execute_kernel(TensorInfo src_tensor_info, TensorInfo weight_tensor_info, TensorInfo bias_tensor_info, TensorInfo dst_tensor_info, const WeightsInfo weights_info,
                                       const PadStrideInfo &conv_info,
                                       const Size2D        &dilation)
     {
-        this->conv->configure(&src_tensor_info, &weight_tensor_info, &bias_tensor_info, &dst_tensor_info, conv_info, weights_info, dilation);
+        this->conv->configure(&src_tensor_info, &weight_tensor_info, &bias_tensor_info, &dst_tensor_info, conv_info, weights_info, dilation, ActivationLayerInfo(), enable_fast_math);
 
         // Allocate input tensors
         auto             src                 = create_tensor<TensorClass>(src_tensor_info);
@@ -624,8 +624,8 @@ class VariableWeightsFixture : public VariableWeightsFixtureBaseClass<Convolutio
     }
 };
 
-template <typename ConvolutionFunction, typename TensorClass, typename AccessorType, typename ScalarType>
-class VariableWeightsFixtureNEInterface : public VariableWeightsFixtureBaseClass<ConvolutionFunction, TensorClass, AccessorType, ScalarType>
+template <typename ConvolutionFunction, typename TensorClass, typename AccessorType, typename ScalarType, bool enable_fast_math>
+class VariableWeightsFixtureNEInterface : public VariableWeightsFixtureBaseClass<ConvolutionFunction, TensorClass, AccessorType, ScalarType, enable_fast_math>
 {
     void configure_and_execute_kernel(TensorInfo src_tensor_info, TensorInfo weight_tensor_info, TensorInfo bias_tensor_info, TensorInfo dst_tensor_info, const WeightsInfo weights_info,
                                       const PadStrideInfo &conv_info,
@@ -644,7 +644,7 @@ class VariableWeightsFixtureNEInterface : public VariableWeightsFixtureBaseClass
         // Allocate destination tensor
         this->_target = create_tensor<TensorClass>(dst_tensor_info);
         this->_target.allocator()->allocate();
-        this->conv->configure(&src, &weights_transformed, &bias, &(this->_target), conv_info, weights_info, dilation);
+        this->conv->configure(&src, &weights_transformed, &bias, &(this->_target), conv_info, weights_info, dilation, ActivationLayerInfo(), enable_fast_math);
         // Prepare source and biases that are left unchanged.
         this->fill(AccessorType(src), 0);
         this->fill(AccessorType(bias), 1);
@@ -664,7 +664,7 @@ class VariableWeightsFixtureNEInterface : public VariableWeightsFixtureBaseClass
     }
 };
 
-template <typename ConvolutionClass>
+template <typename ConvolutionClass, bool enable_fast_math>
 class HasOptImplFixture : public framework::Fixture
 {
 public:
@@ -672,14 +672,15 @@ public:
     void setup(DataType data_type, arm_compute::WeightFormat query_weight_format)
     {
         auto              conv        = std::make_unique<ConvolutionClass>();
-        const auto        src_info    = TensorInfo(TensorShape(1U, 5U, 2U), 1, data_type, DataLayout::NHWC);
-        const auto        weight_info = TensorInfo(TensorShape(1U, 3U, 2U, 3U), 1, data_type, DataLayout::NHWC);
-        const auto        bias_info   = TensorInfo(TensorShape(3U), 1, data_type, DataLayout::NHWC);
-        auto              dst_info    = TensorInfo(TensorShape(1U, 7U, 3U), 1, data_type, DataLayout::NHWC);
-        const auto        conv_info   = PadStrideInfo(1, 1, 0, 0, 2, 2, DimensionRoundingType::FLOOR);
-        const WeightsInfo weights_info(false, 3U, 3U, 1U, false, query_weight_format);
+        const auto        src_info    = TensorInfo(TensorShape(56U, 56U, 64U), 1, data_type, DataLayout::NHWC);
+        const auto        weight_info = TensorInfo(TensorShape(64, 3U, 3U, 64U), 1, enable_fast_math ? DataType::BFLOAT16 : data_type, DataLayout::NHWC);
+        const auto        bias_info   = TensorInfo(TensorShape(64U), 1, data_type, DataLayout::NHWC);
+        auto              dst_info    = TensorInfo(TensorShape(56U, 56U, 64U), 1, data_type, DataLayout::NHWC);
+        const auto        conv_info   = PadStrideInfo(1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR);
+        const WeightsInfo weights_info(false, 3U, 3U, 64U, false, query_weight_format);
         _kernel_found = bool(ConvolutionClass::has_opt_impl(_computed_weight_format, &src_info, &weight_info,
-                                                            &bias_info, &dst_info, conv_info, weights_info));
+                                                            &bias_info, &dst_info, conv_info, weights_info,
+                                                            /*dilation*/ Size2D(1U, 1U), /*act_info*/ ActivationLayerInfo(), enable_fast_math));
     }
 
 protected: