COMPMID-450 Add YOLOV2 benchmark tests

* Migrate BatchNormalizationLayer to new benchmark system.
* Add YOLOV2 benchmark tests.
* Fix F16 type issue in activation_layer cl kernel.
* Separate precommit tests from nightly tests.

Change-Id: I3f206e3f7469be6749d630ede8dcc9fb399de8b0
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/81582
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 0 insertions, 193 deletions

diff --git a/tests/datasets_new/ActivationLayerDataset.h b/tests/datasets_new/ActivationLayerDataset.h
deleted file mode 100644
index a6b882fde2..0000000000
--- a/tests/datasets_new/ActivationLayerDataset.h
+++ /dev/null
@@ -1,193 +0,0 @@
-/*
- * Copyright (c) 2017 ARM Limited.
- *
- * SPDX-License-Identifier: MIT
- *
- * Permission is hereby granted, free of charge, to any person obtaining a copy
- * of this software and associated documentation files (the "Software"), to
- * deal in the Software without restriction, including without limitation the
- * rights to use, copy, modify, merge, publish, distribute, sublicense, and/or
- * sell copies of the Software, and to permit persons to whom the Software is
- * furnished to do so, subject to the following conditions:
- *
- * The above copyright notice and this permission notice shall be included in all
- * copies or substantial portions of the Software.
- *
- * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
- * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
- * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
- * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
- * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
- * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
- * SOFTWARE.
- */
-#ifndef ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET
-#define ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET
-
-#include "framework/datasets/Datasets.h"
-
-#include "tests/TypePrinter.h"
-
-#include "arm_compute/core/TensorShape.h"
-#include "arm_compute/core/Types.h"
-
-namespace arm_compute
-{
-namespace test
-{
-namespace datasets
-{
-class AlexNetActivationLayerDataset final : public
-    framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
-{
-public:
-    AlexNetActivationLayerDataset()
-        : CartesianProductDataset
-    {
-        framework::dataset::make("Shape", {
-            TensorShape(55U, 55U, 96U), TensorShape(27U, 27U, 256U),
-            TensorShape(13U, 13U, 384U), TensorShape(13U, 13U, 256U),
-            TensorShape(4096U) }),
-        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
-    }
-    {
-    }
-    AlexNetActivationLayerDataset(AlexNetActivationLayerDataset &&) = default;
-    ~AlexNetActivationLayerDataset()                                = default;
-};
-
-class LeNet5ActivationLayerDataset final : public
-    framework::dataset::CartesianProductDataset<framework::dataset::SingletonDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
-{
-public:
-    LeNet5ActivationLayerDataset()
-        : CartesianProductDataset
-    {
-        framework::dataset::make("Shape", TensorShape(500U)),
-        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
-    }
-    {
-    }
-    LeNet5ActivationLayerDataset(LeNet5ActivationLayerDataset &&) = default;
-    ~LeNet5ActivationLayerDataset()                               = default;
-};
-
-class GoogLeNetActivationLayerDataset final : public
-    framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
-{
-public:
-    GoogLeNetActivationLayerDataset()
-        : CartesianProductDataset
-    {
-        framework::dataset::make("Shape", { // conv1/relu_7x7
-            TensorShape(112U, 112U, 64U),
-            // conv2/relu_3x3_reduce
-            TensorShape(56U, 56U, 64U),
-            // conv2/relu_3x3
-            TensorShape(56U, 56U, 192U),
-            // inception_3a/relu_1x1, inception_3b/relu_pool_proj
-            TensorShape(28U, 28U, 64U),
-            // inception_3a/relu_3x3_reduce, inception_3b/relu_5x5
-            TensorShape(28U, 28U, 96U),
-            // inception_3a/relu_3x3, inception_3b/relu_1x1, inception_3b/relu_3x3_reduce
-            TensorShape(28U, 28U, 128U),
-            // inception_3a/relu_5x5_reduce
-            TensorShape(28U, 28U, 16U),
-            // inception_3a/relu_5x5, inception_3a/relu_pool_proj, inception_3b/relu_5x5_reduce
-            TensorShape(28U, 28U, 32U),
-            // inception_3b/relu_3x3
-            TensorShape(28U, 28U, 192U),
-            // inception_4a/relu_1x1
-            TensorShape(14U, 14U, 192U),
-            // inception_4a/relu_3x3_reduce
-            TensorShape(14U, 14U, 96U),
-            // inception_4a/relu_3x3
-            TensorShape(14U, 14U, 208U),
-            // inception_4a/relu_5x5_reduce
-            TensorShape(14U, 14U, 16U),
-            // inception_4a/relu_5x5
-            TensorShape(14U, 14U, 48U),
-            // inception_4a/relu_pool_proj, inception_4b/relu_5x5, inception_4b/relu_pool_proj, inception_4c/relu_5x5, inception_4c/relu_pool_proj, inception_4d/relu_5x5, inception_4d/relu_pool_proj
-            TensorShape(14U, 14U, 64U),
-            // inception_4b/relu_1x1, inception_4e/relu_3x3_reduce
-            TensorShape(14U, 14U, 160U),
-            // inception_4b/relu_3x3_reduce, inception_4d/relu_1x1
-            TensorShape(14U, 14U, 112U),
-            // inception_4b/relu_3x3
-            TensorShape(14U, 14U, 224U),
-            // inception_4b/relu_5x5_reduce, inception_4c/relu_5x5_reduce
-            TensorShape(14U, 14U, 24U),
-            // inception_4c/relu_1x1, inception_4c/relu_3x3_reduce, inception_4e/relu_5x5, inception_4e/relu_pool_proj
-            TensorShape(14U, 14U, 128U),
-            // inception_4c/relu_3x3, inception_4e/relu_1x1
-            TensorShape(14U, 14U, 256U),
-            // inception_4d/relu_3x3_reduce
-            TensorShape(14U, 14U, 144U),
-            // inception_4d/relu_3x3
-            TensorShape(14U, 14U, 288U),
-            // inception_4d/relu_5x5_reduce, inception_4e/relu_5x5_reduce
-            TensorShape(14U, 14U, 32U),
-            // inception_4e/relu_3x3
-            TensorShape(14U, 14U, 320U),
-            // inception_5a/relu_1x1
-            TensorShape(7U, 7U, 256U),
-            // inception_5a/relu_3x3_reduce
-            TensorShape(7U, 7U, 160U),
-            // inception_5a/relu_3x3
-            TensorShape(7U, 7U, 320U),
-            // inception_5a/relu_5x5_reduce
-            TensorShape(7U, 7U, 32U),
-            // inception_5a/relu_5x5, inception_5a/relu_pool_proj, inception_5b/relu_5x5, inception_5b/relu_pool_proj
-            TensorShape(7U, 7U, 128U),
-            // inception_5b/relu_1x1, inception_5b/relu_3x3
-            TensorShape(7U, 7U, 384U),
-            // inception_5b/relu_3x3_reduce
-            TensorShape(7U, 7U, 192U),
-            // inception_5b/relu_5x5_reduce
-            TensorShape(7U, 7U, 48U) }),
-        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
-    }
-    {
-    }
-    GoogLeNetActivationLayerDataset(GoogLeNetActivationLayerDataset &&) = default;
-    ~GoogLeNetActivationLayerDataset()                                  = default;
-};
-
-class SqueezeNetActivationLayerDataset final : public
-    framework::dataset::CartesianProductDataset<framework::dataset::InitializerListDataset<TensorShape>, framework::dataset::SingletonDataset<ActivationLayerInfo>>
-{
-public:
-    SqueezeNetActivationLayerDataset()
-        : CartesianProductDataset
-    {
-        framework::dataset::make("Shape", { // relu_conv1
-            TensorShape(111U, 111U, 64U),
-            // fire2/relu_squeeze1x1, fire3/relu_squeeze1x1
-            TensorShape(55U, 55U, 16U),
-            // fire2/relu_expand1x1, fire2/relu_expand3x3, fire3/relu_expand1x1, fire3/relu_expand3x3
-            TensorShape(55U, 55U, 64U),
-            // fire4/relu_squeeze1x1, fire5/relu_squeeze1x1
-            TensorShape(27U, 27U, 32U),
-            // fire4/relu_expand1x1, fire4/relu_expand3x3, fire5/relu_expand1x1, fire5/relu_expand3x3
-            TensorShape(27U, 27U, 128U),
-            // fire6/relu_squeeze1x1, fire7/relu_squeeze1x1
-            TensorShape(13U, 13U, 48U),
-            // fire6/relu_expand1x1, fire6/relu_expand3x3, fire7/relu_expand1x1, fire7/relu_expand3x3
-            TensorShape(13U, 13U, 192U),
-            // fire8/relu_squeeze1x1, fire9/relu_squeeze1x1
-            TensorShape(13U, 13U, 64U),
-            // fire8/relu_expand1x1, fire8/relu_expand3x3, fire9/relu_expand1x1, fire9/relu_expand3x3
-            TensorShape(13U, 13U, 256U),
-            // relu_conv10
-            TensorShape(13U, 13U, 1000U) }),
-        framework::dataset::make("Info", ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
-    }
-    {
-    }
-    SqueezeNetActivationLayerDataset(SqueezeNetActivationLayerDataset &&) = default;
-    ~SqueezeNetActivationLayerDataset()                                   = default;
-};
-} // namespace datasets
-} // namespace test
-} // namespace arm_compute
-#endif /* ARM_COMPUTE_TEST_ACTIVATION_LAYER_DATASET */