COMPMID-970 : Remove QS8 / QS16 support
Removed Fixed point position arguments from test sources
Change-Id: I8343724723b71611fd501ed34de0866d3fb60e7e
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/136382
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/tests/benchmark/fixtures/ActivationLayerFixture.h b/tests/benchmark/fixtures/ActivationLayerFixture.h
index d46ef28..a82861f 100644
--- a/tests/benchmark/fixtures/ActivationLayerFixture.h
+++ b/tests/benchmark/fixtures/ActivationLayerFixture.h
@@ -48,10 +48,9 @@
shape.set(shape.num_dimensions(), batches);
// Create tensors
- const int fixed_point_position = 4;
const QuantizationInfo q_info(0.5f, -10);
- src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, q_info);
- dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, q_info);
+ src = create_tensor<TensorType>(shape, data_type, 1, q_info);
+ dst = create_tensor<TensorType>(shape, data_type, 1, q_info);
// Create and configure function
act_layer.configure(&src, &dst, info);
diff --git a/tests/benchmark/fixtures/AlexNetFixture.h b/tests/benchmark/fixtures/AlexNetFixture.h
index 46ac61b..4662feb 100644
--- a/tests/benchmark/fixtures/AlexNetFixture.h
+++ b/tests/benchmark/fixtures/AlexNetFixture.h
@@ -53,10 +53,9 @@
template <typename...>
void setup(DataType data_type, int batches)
{
- constexpr bool weights_reshaped = false;
- constexpr int fixed_point_position = 4;
+ constexpr bool weights_reshaped = false;
- network.init(data_type, fixed_point_position, batches, weights_reshaped);
+ network.init(data_type, batches, weights_reshaped);
network.build();
network.allocate();
}
diff --git a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
index ae8f8a7..42adefe 100644
--- a/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
+++ b/tests/benchmark/fixtures/BatchNormalizationLayerFixture.h
@@ -45,7 +45,7 @@
void setup(TensorShape tensor_shape, TensorShape param_shape, float epsilon, bool use_gamma, bool use_beta, ActivationLayerInfo act_info, DataType data_type, DataLayout data_layout, int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
tensor_shape.set(tensor_shape.num_dimensions(), batches);
if(data_layout == DataLayout::NHWC)
{
@@ -53,12 +53,12 @@
}
// Create tensors
- src = create_tensor<TensorType>(tensor_shape, data_type, 1, fixed_point_position, QuantizationInfo(), data_layout);
- dst = create_tensor<TensorType>(tensor_shape, data_type, 1, fixed_point_position, QuantizationInfo(), data_layout);
- mean = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position);
- variance = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position);
- beta = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position);
- gamma = create_tensor<TensorType>(param_shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(tensor_shape, data_type, 1, QuantizationInfo(), data_layout);
+ dst = create_tensor<TensorType>(tensor_shape, data_type, 1, QuantizationInfo(), data_layout);
+ mean = create_tensor<TensorType>(param_shape, data_type, 1);
+ variance = create_tensor<TensorType>(param_shape, data_type, 1);
+ beta = create_tensor<TensorType>(param_shape, data_type, 1);
+ gamma = create_tensor<TensorType>(param_shape, data_type, 1);
// Create and configure function
TensorType *beta_ptr = use_beta ? &beta : nullptr;
diff --git a/tests/benchmark/fixtures/ConvolutionLayerFixture.h b/tests/benchmark/fixtures/ConvolutionLayerFixture.h
index 511daf7..338a021 100644
--- a/tests/benchmark/fixtures/ConvolutionLayerFixture.h
+++ b/tests/benchmark/fixtures/ConvolutionLayerFixture.h
@@ -46,16 +46,16 @@
int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
src_shape.set(3 /* batch */, batches);
dst_shape.set(3 /* batch */, batches);
DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position);
- weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
- biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(src_shape, data_type, 1);
+ weights = create_tensor<TensorType>(weights_shape, data_type, 1);
+ biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
conv_layer.configure(&src, &weights, &biases, &dst, info, WeightsInfo(), dilation, act_info);
diff --git a/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h b/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h
index bd4b404..292adde 100644
--- a/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h
+++ b/tests/benchmark/fixtures/DepthConcatenateLayerFixture.h
@@ -95,12 +95,12 @@
for(const auto &shape : src_shapes)
{
- _srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1, _fractional_bits));
+ _srcs.emplace_back(create_tensor<TensorType>(shape, data_type, 1));
src_ptrs.emplace_back(&_srcs.back());
}
TensorShape dst_shape = calculate_depth_concatenate_shape(src_ptrs);
- _dst = create_tensor<TensorType>(dst_shape, data_type, 1, _fractional_bits);
+ _dst = create_tensor<TensorType>(dst_shape, data_type, 1);
_depth_concat.configure(src_ptrs, &_dst);
@@ -139,7 +139,6 @@
std::vector<TensorType> _srcs{};
TensorType _dst{};
Function _depth_concat{};
- int _fractional_bits{ 1 };
};
} // namespace benchmark
} // namespace test
diff --git a/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h b/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h
index 9276431..48ea038 100644
--- a/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h
+++ b/tests/benchmark/fixtures/DepthwiseConvolutionLayerFixture.h
@@ -57,15 +57,15 @@
weights_shape.set(2, dst_shape.z());
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
src_shape.set(3 /* batch */, batches);
dst_shape.set(3 /* batch */, batches);
// Create tensors
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position, QuantizationInfo(0.5f, 10));
- weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position, QuantizationInfo(0.5f, 10));
- biases = create_tensor<TensorType>(TensorShape(weights_shape[2]), is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position, QuantizationInfo(0.5f, 10));
+ src = create_tensor<TensorType>(src_shape, data_type, 1, QuantizationInfo(0.5f, 10));
+ weights = create_tensor<TensorType>(weights_shape, data_type, 1, QuantizationInfo(0.5f, 10));
+ biases = create_tensor<TensorType>(TensorShape(weights_shape[2]), is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type, 1);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1, QuantizationInfo(0.5f, 10));
// Create and configure function
depth_conv.configure(&src, &weights, &biases, &dst, info);
diff --git a/tests/benchmark/fixtures/DepthwiseSeparableConvolutionLayerFixture.h b/tests/benchmark/fixtures/DepthwiseSeparableConvolutionLayerFixture.h
index ef1a407..927bb4d 100644
--- a/tests/benchmark/fixtures/DepthwiseSeparableConvolutionLayerFixture.h
+++ b/tests/benchmark/fixtures/DepthwiseSeparableConvolutionLayerFixture.h
@@ -47,18 +47,18 @@
PadStrideInfo pad_stride_depthwise_info, PadStrideInfo pad_stride_pointwise_info, DataType data_type, int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
src_shape.set(3 /* batch */, batches);
depthwise_out_shape.set(3 /* batch */, batches);
dst_shape.set(3 /* batch */, batches);
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position);
- depthwise_weights = create_tensor<TensorType>(depthwise_weights_shape, data_type, 1, fixed_point_position);
- depthwise_biases = create_tensor<TensorType>(depthwise_biases_shape, data_type, 1, fixed_point_position);
- depthwise_out = create_tensor<TensorType>(depthwise_out_shape, data_type, 1, fixed_point_position);
- pointwise_weights = create_tensor<TensorType>(pointwise_weights_shape, data_type, 1, fixed_point_position);
- pointwise_biases = create_tensor<TensorType>(pointwise_biases_shape, data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(src_shape, data_type, 1);
+ depthwise_weights = create_tensor<TensorType>(depthwise_weights_shape, data_type, 1);
+ depthwise_biases = create_tensor<TensorType>(depthwise_biases_shape, data_type, 1);
+ depthwise_out = create_tensor<TensorType>(depthwise_out_shape, data_type, 1);
+ pointwise_weights = create_tensor<TensorType>(pointwise_weights_shape, data_type, 1);
+ pointwise_biases = create_tensor<TensorType>(pointwise_biases_shape, data_type, 1);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
depth_sep_conv_layer.configure(&src, &depthwise_weights, &depthwise_biases, &depthwise_out, &pointwise_weights, &pointwise_biases, &dst, pad_stride_depthwise_info, pad_stride_pointwise_info);
diff --git a/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h b/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h
index 419f6dd..f74f0ec 100644
--- a/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h
+++ b/tests/benchmark/fixtures/DirectConvolutionLayerFixture.h
@@ -49,16 +49,16 @@
ARM_COMPUTE_UNUSED(dilation);
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
src_shape.set(3 /* batch */, batches);
dst_shape.set(3 /* batch */, batches);
DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position);
- weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
- biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(src_shape, data_type, 1);
+ weights = create_tensor<TensorType>(weights_shape, data_type, 1);
+ biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
conv_layer.configure(&src, &weights, &biases, &dst, info, act_info);
diff --git a/tests/benchmark/fixtures/FlattenLayerFixture.h b/tests/benchmark/fixtures/FlattenLayerFixture.h
index 749fa0d..3d46989 100644
--- a/tests/benchmark/fixtures/FlattenLayerFixture.h
+++ b/tests/benchmark/fixtures/FlattenLayerFixture.h
@@ -46,11 +46,9 @@
TensorShape shape_flatten(shape);
shape_flatten.collapse(3);
- const unsigned int fixed_point_position = is_data_type_fixed_point(data_type) ? 4 : 0;
-
// Create tensors
- src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(shape_flatten, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(shape, data_type, 1);
+ dst = create_tensor<TensorType>(shape_flatten, data_type, 1);
// Create and configure function
flatten_func.configure(&src, &dst);
diff --git a/tests/benchmark/fixtures/FullyConnectedLayerFixture.h b/tests/benchmark/fixtures/FullyConnectedLayerFixture.h
index e7a5260..caef5be 100644
--- a/tests/benchmark/fixtures/FullyConnectedLayerFixture.h
+++ b/tests/benchmark/fixtures/FullyConnectedLayerFixture.h
@@ -45,15 +45,15 @@
void setup(TensorShape src_shape, TensorShape weights_shape, TensorShape biases_shape, TensorShape dst_shape, DataType data_type, int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
src_shape.set(src_shape.num_dimensions() /* batch */, batches);
dst_shape.set(dst_shape.num_dimensions() /* batch */, batches);
// Create tensors
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position);
- weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
- biases = create_tensor<TensorType>(biases_shape, data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(src_shape, data_type, 1);
+ weights = create_tensor<TensorType>(weights_shape, data_type, 1);
+ biases = create_tensor<TensorType>(biases_shape, data_type, 1);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
fc_layer.configure(&src, &weights, &biases, &dst);
diff --git a/tests/benchmark/fixtures/GEMMFixture.h b/tests/benchmark/fixtures/GEMMFixture.h
index f706f3e..7628abc 100644
--- a/tests/benchmark/fixtures/GEMMFixture.h
+++ b/tests/benchmark/fixtures/GEMMFixture.h
@@ -44,13 +44,11 @@
template <typename...>
void setup(TensorShape shape_a, TensorShape shape_b, TensorShape shape_c, TensorShape shape_dst, float alpha, float beta, DataType data_type, bool reshape_b_only_on_first_run)
{
- constexpr int fixed_point_position = 4;
-
// Create tensors
- a = create_tensor<TensorType>(shape_a, data_type, 1, fixed_point_position);
- b = create_tensor<TensorType>(shape_b, data_type, 1, fixed_point_position);
- c = create_tensor<TensorType>(shape_c, data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(shape_dst, data_type, 1, fixed_point_position);
+ a = create_tensor<TensorType>(shape_a, data_type, 1);
+ b = create_tensor<TensorType>(shape_b, data_type, 1);
+ c = create_tensor<TensorType>(shape_c, data_type, 1);
+ dst = create_tensor<TensorType>(shape_dst, data_type, 1);
// Create and configure function
gemm.configure(&a, &b, &c, &dst, alpha, beta, GEMMInfo(false, false, reshape_b_only_on_first_run));
diff --git a/tests/benchmark/fixtures/GEMMInterleave4x4Fixture.h b/tests/benchmark/fixtures/GEMMInterleave4x4Fixture.h
index 793c540..c8e6f4a 100644
--- a/tests/benchmark/fixtures/GEMMInterleave4x4Fixture.h
+++ b/tests/benchmark/fixtures/GEMMInterleave4x4Fixture.h
@@ -44,14 +44,12 @@
template <typename...>
void setup(size_t x, size_t y, DataType data_type)
{
- constexpr int fixed_point_position = 4;
-
const TensorShape shape_a(x, y);
const TensorShape shape_b(static_cast<size_t>(x * 4.f), static_cast<size_t>(std::ceil(y / 4.f)));
// Create tensors
- a = create_tensor<TensorType>(shape_a, data_type, 1, fixed_point_position);
- b = create_tensor<TensorType>(shape_b, data_type, 1, fixed_point_position);
+ a = create_tensor<TensorType>(shape_a, data_type, 1);
+ b = create_tensor<TensorType>(shape_b, data_type, 1);
// Create and configure function
gemm.configure(&a, &b);
diff --git a/tests/benchmark/fixtures/GEMMLowpFixture.h b/tests/benchmark/fixtures/GEMMLowpFixture.h
index b5381b0..46a2f5c 100644
--- a/tests/benchmark/fixtures/GEMMLowpFixture.h
+++ b/tests/benchmark/fixtures/GEMMLowpFixture.h
@@ -53,9 +53,9 @@
// Note: The offsets for matrix A and matrix B are set to 0 in order to skip the computation for the offset contribution
// Create tensors
- a = create_tensor<TensorType>(shape_a, DataType::QASYMM8, 1, 0, QuantizationInfo(1.0f / 255.0f, 0));
- b = create_tensor<TensorType>(shape_b, DataType::QASYMM8, 1, 0, QuantizationInfo(1.0f / 255.0f, 0));
- c = create_tensor<TensorType>(shape_dst, DataType::S32, 1, 0, QuantizationInfo(1.0f / 255.0f, 0));
+ a = create_tensor<TensorType>(shape_a, DataType::QASYMM8, 1, QuantizationInfo(1.0f / 255.0f, 0));
+ b = create_tensor<TensorType>(shape_b, DataType::QASYMM8, 1, QuantizationInfo(1.0f / 255.0f, 0));
+ c = create_tensor<TensorType>(shape_dst, DataType::S32, 1, QuantizationInfo(1.0f / 255.0f, 0));
// Create and configure function
gemmlowp.configure(&a, &b, &c);
diff --git a/tests/benchmark/fixtures/NormalizationLayerFixture.h b/tests/benchmark/fixtures/NormalizationLayerFixture.h
index 7742dca..4331506 100644
--- a/tests/benchmark/fixtures/NormalizationLayerFixture.h
+++ b/tests/benchmark/fixtures/NormalizationLayerFixture.h
@@ -45,12 +45,12 @@
void setup(TensorShape shape, NormalizationLayerInfo info, DataType data_type, int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
shape.set(shape.num_dimensions(), batches);
// Create tensors
- src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(shape, data_type, 1);
+ dst = create_tensor<TensorType>(shape, data_type, 1);
// Create and configure function
norm_layer.configure(&src, &dst, info);
diff --git a/tests/benchmark/fixtures/PoolingLayerFixture.h b/tests/benchmark/fixtures/PoolingLayerFixture.h
index 5a1a296..cbcfe2e 100644
--- a/tests/benchmark/fixtures/PoolingLayerFixture.h
+++ b/tests/benchmark/fixtures/PoolingLayerFixture.h
@@ -48,7 +48,6 @@
void setup(TensorShape src_shape, PoolingLayerInfo info, DataType data_type, DataLayout data_layout, int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
// Permute shape if NHWC format
if(data_layout == DataLayout::NHWC)
@@ -56,7 +55,7 @@
permute(src_shape, PermutationVector(2U, 0U, 1U));
}
- TensorInfo src_info(src_shape, 1, data_type, fixed_point_position);
+ TensorInfo src_info(src_shape, 1, data_type);
src_info.set_data_layout(data_layout);
TensorShape dst_shape = compute_pool_shape(src_info, info);
@@ -65,8 +64,8 @@
dst_shape.set(dst_shape.num_dimensions(), batches);
// Create tensors
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position, QuantizationInfo(), data_layout);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position, QuantizationInfo(), data_layout);
+ src = create_tensor<TensorType>(src_shape, data_type, 1, QuantizationInfo(), data_layout);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1, QuantizationInfo(), data_layout);
// Create and configure function
pool_layer.configure(&src, &dst, info);
diff --git a/tests/benchmark/fixtures/ROIPoolingLayerFixture.h b/tests/benchmark/fixtures/ROIPoolingLayerFixture.h
index 4adfa44..fa4a5b7 100644
--- a/tests/benchmark/fixtures/ROIPoolingLayerFixture.h
+++ b/tests/benchmark/fixtures/ROIPoolingLayerFixture.h
@@ -47,8 +47,8 @@
void setup(TensorShape shape, const ROIPoolingLayerInfo pool_info, unsigned int num_rois, DataType data_type, int batches)
{
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
- TensorShape shape_dst;
+
+ TensorShape shape_dst;
shape.set(shape.num_dimensions(), batches);
shape_dst.set(0, pool_info.pooled_width());
shape_dst.set(1, pool_info.pooled_height());
@@ -56,8 +56,8 @@
shape_dst.set(3, num_rois);
// Create tensors
- src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(shape_dst, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(shape, data_type, 1);
+ dst = create_tensor<TensorType>(shape_dst, data_type, 1);
// Create random ROIs
std::vector<ROI> rois = generate_random_rois(shape, pool_info, num_rois, 0U);
diff --git a/tests/benchmark/fixtures/SoftmaxLayerFixture.h b/tests/benchmark/fixtures/SoftmaxLayerFixture.h
index 4f6dde8..4d092f7 100644
--- a/tests/benchmark/fixtures/SoftmaxLayerFixture.h
+++ b/tests/benchmark/fixtures/SoftmaxLayerFixture.h
@@ -45,11 +45,9 @@
template <typename...>
void setup(TensorShape shape, DataType data_type)
{
- const unsigned int fixed_point_position = 4;
-
// Create tensors
- src = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, QuantizationInfo(1.f / 256, 10));
- dst = create_tensor<TensorType>(shape, data_type, 1, fixed_point_position, QuantizationInfo(1.f / 256, 0));
+ src = create_tensor<TensorType>(shape, data_type, 1, QuantizationInfo(1.f / 256, 10));
+ dst = create_tensor<TensorType>(shape, data_type, 1, QuantizationInfo(1.f / 256, 0));
ARM_COMPUTE_EXPECT(src.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(dst.info()->is_resizable(), framework::LogLevel::ERRORS);
diff --git a/tests/benchmark/fixtures/WinogradConvolutionLayerFixture.h b/tests/benchmark/fixtures/WinogradConvolutionLayerFixture.h
index 8ed75af..5f44517 100644
--- a/tests/benchmark/fixtures/WinogradConvolutionLayerFixture.h
+++ b/tests/benchmark/fixtures/WinogradConvolutionLayerFixture.h
@@ -48,16 +48,16 @@
ARM_COMPUTE_UNUSED(dilation);
// Set batched in source and destination shapes
- const unsigned int fixed_point_position = 4;
+
src_shape.set(3 /* batch */, batches);
dst_shape.set(3 /* batch */, batches);
DataType bias_data_type = is_data_type_quantized_asymmetric(data_type) ? DataType::S32 : data_type;
// Create tensors
- src = create_tensor<TensorType>(src_shape, data_type, 1, fixed_point_position);
- weights = create_tensor<TensorType>(weights_shape, data_type, 1, fixed_point_position);
- biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1, fixed_point_position);
- dst = create_tensor<TensorType>(dst_shape, data_type, 1, fixed_point_position);
+ src = create_tensor<TensorType>(src_shape, data_type, 1);
+ weights = create_tensor<TensorType>(weights_shape, data_type, 1);
+ biases = create_tensor<TensorType>(biases_shape, bias_data_type, 1);
+ dst = create_tensor<TensorType>(dst_shape, data_type, 1);
// Create and configure function
conv_layer.configure(&src, &weights, &biases, &dst, info, act_info);