COMPMID-514 (3RDPARTY_UPDATE)(DATA_UPDATE) Add support to load .npy data

* Add tensorflow_data_extractor script.
* Incorporate 3rdparty npy reader libnpy.
* Port AlexNet system test to validation_new.
* Port LeNet5 system test to validation_new.
* Update 3rdparty/ and data/ submodules.

Change-Id: I156d060fe9185cd8db810b34bf524cbf5cb34f61
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/84914
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>

1 files changed, 115 insertions, 0 deletions

diff --git a/tests/validation/CL/SYSTEM/AlexNet.cpp b/tests/validation/CL/SYSTEM/AlexNet.cpp
new file mode 100644
index 0000000000..d7dd62d4f2
--- /dev/null
+++ b/tests/validation/CL/SYSTEM/AlexNet.cpp
@@ -0,0 +1,115 @@
+/*
+ * 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.
+ */
+#ifdef INTERNAL_ONLY //FIXME Delete this file before the release
+
+#include "arm_compute/runtime/CL/CLSubTensor.h"
+#include "arm_compute/runtime/CL/functions/CLActivationLayer.h"
+#include "arm_compute/runtime/CL/functions/CLConvolutionLayer.h"
+#include "arm_compute/runtime/CL/functions/CLDirectConvolutionLayer.h"
+#include "arm_compute/runtime/CL/functions/CLFullyConnectedLayer.h"
+#include "arm_compute/runtime/CL/functions/CLNormalizationLayer.h"
+#include "arm_compute/runtime/CL/functions/CLPoolingLayer.h"
+#include "arm_compute/runtime/CL/functions/CLSoftmaxLayer.h"
+#include "tests/CL/CLAccessor.h"
+#include "tests/framework/Asserts.h"
+#include "tests/framework/Macros.h"
+#include "tests/networks/AlexNetNetwork.h"
+#include "tests/validation/Validation.h"
+
+#include <string>
+#include <vector>
+
+namespace arm_compute
+{
+namespace test
+{
+namespace validation
+{
+namespace
+{
+using CLAlexNetModel = networks::AlexNetNetwork<ICLTensor,
+      CLTensor,
+      CLSubTensor,
+      CLAccessor,
+      CLActivationLayer,
+      CLConvolutionLayer,
+      CLDirectConvolutionLayer,
+      CLFullyConnectedLayer,
+      CLNormalizationLayer,
+      CLPoolingLayer,
+      CLSoftmaxLayer>;
+std::vector<unsigned int> compute_alexnet(DataType dt, unsigned int batches, std::string input_file)
+{
+    std::vector<std::string> weight_files = { "cnn_data/alexnet_model/conv1_w.npy",
+                                              "cnn_data/alexnet_model/conv2_w.npy",
+                                              "cnn_data/alexnet_model/conv3_w.npy",
+                                              "cnn_data/alexnet_model/conv4_w.npy",
+                                              "cnn_data/alexnet_model/conv5_w.npy",
+                                              "cnn_data/alexnet_model/fc6_w.npy",
+                                              "cnn_data/alexnet_model/fc7_w.npy",
+                                              "cnn_data/alexnet_model/fc8_w.npy"
+                                            };
+
+    std::vector<std::string> bias_files = { "cnn_data/alexnet_model/conv1_b.npy",
+                                            "cnn_data/alexnet_model/conv2_b.npy",
+                                            "cnn_data/alexnet_model/conv3_b.npy",
+                                            "cnn_data/alexnet_model/conv4_b.npy",
+                                            "cnn_data/alexnet_model/conv5_b.npy",
+                                            "cnn_data/alexnet_model/fc6_b.npy",
+                                            "cnn_data/alexnet_model/fc7_b.npy",
+                                            "cnn_data/alexnet_model/fc8_b.npy"
+                                          };
+    CLAlexNetModel network{};
+    network.init(dt, 4, batches);
+    network.build();
+    network.allocate();
+    network.fill(weight_files, bias_files);
+    network.feed(std::move(input_file));
+    network.run();
+
+    return network.get_classifications();
+}
+} // namespace
+
+TEST_SUITE(CL)
+TEST_SUITE(SYSTEM_TESTS)
+
+TEST_CASE(AlexNet, framework::DatasetMode::PRECOMMIT)
+{
+    // Compute alexnet
+    std::vector<unsigned int> classified_labels = compute_alexnet(DataType::F32, 1, "cnn_data/imagenet_data/cat.npy");
+
+    // Expected labels
+    std::vector<unsigned int> expected_labels = { 281 };
+
+    // Validate labels
+    validate(classified_labels, expected_labels);
+}
+
+TEST_SUITE_END()
+TEST_SUITE_END()
+} // namespace validation
+} // namespace test
+} // namespace arm_compute
+#endif /* INTERNAL_ONLY */