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-rw-r--r--src/cpu/kernels/CpuActivationKernel.cpp15
-rw-r--r--tests/validation/fixtures/FFTFixture.h6
2 files changed, 6 insertions, 15 deletions
diff --git a/src/cpu/kernels/CpuActivationKernel.cpp b/src/cpu/kernels/CpuActivationKernel.cpp
index f1e485883c..e8ece26f17 100644
--- a/src/cpu/kernels/CpuActivationKernel.cpp
+++ b/src/cpu/kernels/CpuActivationKernel.cpp
@@ -208,18 +208,9 @@ void CpuActivationKernel::configure(const ITensorInfo *src, ITensorInfo *dst, Ac
Window win;
- if(src->data_layout() != DataLayout::NHWC)
- {
- // Use squashed window
- std::tie(win, _split_dimension) = calculate_squashed_or_max_window(*src);
- ICPPKernel::configure(win);
- }
- else
- {
- // Configure kernel window
- win = calculate_max_window(*src, Steps());
- ICPPKernel::configure(win);
- }
+ // Use squashed window
+ std::tie(win, _split_dimension) = calculate_squashed_or_max_window(*src);
+ ICPPKernel::configure(win);
}
Status CpuActivationKernel::validate(const ITensorInfo *src, const ITensorInfo *dst, const ActivationLayerInfo &act_info)
diff --git a/tests/validation/fixtures/FFTFixture.h b/tests/validation/fixtures/FFTFixture.h
index a70335b6f1..16ac212fcc 100644
--- a/tests/validation/fixtures/FFTFixture.h
+++ b/tests/validation/fixtures/FFTFixture.h
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2019-2021 Arm Limited.
+ * Copyright (c) 2019-2022 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -202,6 +202,8 @@ protected:
TensorType bias = create_tensor<TensorType>(bias_shape, _data_type, 1, QuantizationInfo(), _data_layout);
TensorType dst = create_tensor<TensorType>(output_shape, _data_type, 1, QuantizationInfo(), _data_layout);
+ add_padding_x({ &src, &weights, &bias, &dst }, _data_layout);
+
// Create and configure function
FunctionType conv;
conv.configure(&src, &weights, &bias, &dst, info, act_info, _data_type == DataType::F16);
@@ -211,8 +213,6 @@ protected:
ARM_COMPUTE_ASSERT(bias.info()->is_resizable());
ARM_COMPUTE_ASSERT(dst.info()->is_resizable());
- add_padding_x({ &src, &weights, &bias, &dst }, _data_layout);
-
// Allocate tensors
src.allocator()->allocate();
weights.allocator()->allocate();