Doc Migration from Gitlab (openvinotoolkit#1289)

* doc migration

* fix

* Update FakeQuantize_1.md

* Update performance_benchmarks.md

* Updates graphs for FPGA

* Update performance_benchmarks.md

* Change DL Workbench structure (openvinotoolkit#1)

* Changed DL Workbench structure

* Fixed tags

* fixes

* Update ie_docs.xml

* Update performance_benchmarks_faq.md

* Fixes in DL Workbench layout

* Fixes for CVS-31290

* [DL Workbench] Minor correction

* Fix for CVS-30955

* Added nGraph deprecation notice as requested by Zoe

* fix broken links in api doxy layouts

* CVS-31131 fixes

* Additional fixes

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* Update PAC_Configure.md

PAC DCP 1.2.1 install guide.

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.gitattributes

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 #*.PDF   diff=astextplain
 #*.rtf   diff=astextplain
 #*.RTF   diff=astextplain
+
+*.PNG filter=lfs diff=lfs merge=lfs -text
+*.png filter=lfs diff=lfs merge=lfs -text
+*.jpg filter=lfs diff=lfs merge=lfs -text
+*.gif filter=lfs diff=lfs merge=lfs -text
+*.vsdx filter=lfs diff=lfs merge=lfs -text

docs/HOWTO/add_regression_test_vpu.md

@@ -0,0 +1,83 @@
+# Regression tests howto {#openvino_docs_HOWTO_add_regression_test_vpu}
+
+## Purpose
+
+This document contains instructions for correctly modifying a set of regression tests.
+
+## Common
+
+Regression tests for Myriad and HDDL plugins are on the path:
+`inference-engine/tests/functional/vpu/regression_tests/`
+
+The tests are divided into 4 groups:
+* Classification
+* Detection
+* Raw-results
+* Compilation
+* VPU hetero
+
+Testing  framework – [Google Test](https://github.com/google/googletest/).
+Each group contains [parameterized](https://github.com/google/googletest/blob/master/googletest/docs/advanced.md) tests. The main idea is that to add a new test, you only need to add a new parameter. Except for scenarios different from the generalized case.
+
+## Classsification and Detection tests
+
+These groups contains two cases:
+
+* For generalized scenario (` VpuNoClassificationRegression, VpuNoDetectionRegression`)
+* For specific scenario (` VpuNoClassificationRegressionSpecific, VpuNoDetectionRegressionSpecific`)
+
+### Generalized scenario
+
+If You want test new parameter(batch, precision, model and etc.) then You need to edit the existing initialization of parameterized tests or create a new one.  
+Example of initialization of parameterized tests:
+
+``` c++
+INSTANTIATE_TEST_CASE_P(
+        VPURegTestWithResources_nightly,
+        VpuNoClassificationRegression,
+        Combine(ValuesIn(VpuTestParamsContainer::testingPlugin()),
+                Values(Precision::FP16),
+                Values(1),  // batches
+                Values(true), //IsHwAdaptiveMode
+                Values(false), //DoReshape
+                Values(3, 5, 7), //Resources
+                Values(false), //IsIgnoreStatistic
+                Values(ClassificationSrcParam{ModelName::GoogleNetV1, SourceImages::kCat3, 0.01, Regression::EMean::eValues})),
+        VpuNoClassificationRegression::getTestCaseName);
+```
+
+### Specific scenario
+
+If You need a test to perform some actions that are not provided in the generalized scenario, then add a specific test case. As with the generalized scenario You can change parameters for these tests.  
+Example of specific test case:
+
+``` c++
+TEST_P(VpuNoClassificationRegressionSpecific, onAlexNetWithNetworkConfig) {
+    DISABLE_ON_WINDOWS_IF(HDDL_PLUGIN);
+    DISABLE_IF(do_reshape_);
+
+    if (!hw_adaptive_mode_) {
+        config_[VPU_CONFIG_KEY(NETWORK_CONFIG)] = "data=data,scale=1";
+    }
+
+    assertThat().classificationResultsForInferRequestAPI()
+            .on(SourceImages::kDog2)
+            .withInputPrecision(in_precision_)
+            .times(batch_)
+            .withBatch(batch_)
+            .onModel(ModelName::AlexNet)
+            .setMean(Regression::EMean::eImage)
+            .onFP16()
+            .withTopK(1)
+            .withPluginConfig(config_)
+            .equalToReferenceWithDelta(0.04);
+}
+```
+
+## Raw-results tests
+
+There is no generalized scenario and recommendations are the same as for specific test cases for Classification/Detection groups.
+
+## Compilation tests
+
+The tests are in the `vpu_classification_regression.cpp` file and contains only one scenario ` VpuNoRegressionWithCompilation `. To add a new test just update parameters just as in generalized scenarion of Classification/Detection test groups.

docs/HOWTO/fuzzing-HOWTO.md

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+# Fuzzing howto {#openvino_docs_HOWTO_fuzzing_HOWTO}
+
+## Intended Audience
+
+This document is for a developer who wants to contribute fuzz tests.
+
+## Purpose
+
+This document walks you through creating your first fuzzer, running it and evaluating its quality.
+
+## Prerequisites
+
+- Linux OS or Mac OS.
+
+- [American Fuzzy Loop](http://lcamtuf.coredump.cx/afl/) if building   with GCC.
+
+## Steps
+
+1. Create a fuzz test in the existing project at `./tests/fuzz`. Fuzz test must
+   follow `<test name>-fuzzer.cc` naming scheme and implement a
+   `LLVMFuzzerTestOneInput` entry point.
+
+``` bash
+cat << EOF > ./tests/fuzz/test_name-fuzzer.cc
+#include <stdint.h>
+#include <cstdlib>
+
+extern "C" int LLVMFuzzerTestOneInput(const uint8_t* data, size_t size) {
+  // put your fuzzing code here and use data+size as input.
+  return 0;  // always return 0
+}
+EOF
+```
+
+2. Implement test logic under `LLVMFuzzerTestOneInput`.
+
+See example fuzz test at `tests/fuzz/read_network-fuzzer.cc`.
+
+3. Build fuzz tests with `-DENABLE_FUZZING=ON` flag for cmake.
+
+``` bash
+    mkdir -p build && \
+    (cd build && \
+    CXX=afl-g++ CC=afl-gcc cmake -DCMAKE_BUILD_TYPE=Debug -DENABLE_FUZZING=ON -DENABLE_TESTS=ON .. && \
+    make fuzz --jobs=$(getconf _NPROCESSORS_ONLN))
+```
+
+4. Prepare sample inputs for your fuzz test to teach fuzzer engine on input
+   structure
+
+``` bash
+(cd bin/intel64/Debug && \
+mkdir test_name-corpus && \
+echo sample input > test_name-corpus/in1.txt)
+```
+
+5. Evaluate fuzz test with `afl-fuzz` fuzzing engine
+
+Run fuzz test:
+
+``` bash
+(cd bin/intel64/Debug && \
+afl-fuzz -i test_name-corpus -o test_name-out -- ./test_name-fuzzer @@
+```
+
+While fuzz test is running it prints out statistics. Besides just crashes `uniq
+crashes` and hangs `uniq hangs` you should care about fuzz test quality:
+
+- Fuzz test should be fast - speed of execution `exec speed` should be at least
+  100 exec/s. Speed less than 20 exec/s is not acceptable.
+
+- Fuzz test should be able to explore new code paths `map coverage` and
+  `findings in depth`. Confirm it is increasing while fuzz test is running.
+
+6. Reproduce fuzz test findings
+
+All issues found by fuzz test are stored as a file in output folder specified
+earlier via `-o` afl-fuzz option. To reproduce an issue run fuzz test executable
+with an issue file as an argument.
+
+## Summary
+
+We have created a simple fuzz test, run it and asses its results.
+
+## Extension
+
+Try run parallel fuzzing with the help of
+[afl-utils](https://gitlab.com/rc0r/afl-utils).
+
+## Tips or FAQs
+
+GCC 7 in Ubuntu 18.04 LTS has a
+[defect](https://bugs.launchpad.net/ubuntu/+source/afl/+bug/1774816). Upgrade
+GCC 7 for AFL to work. GCC version `Ubuntu 7.3.0-27ubuntu1~18.04` works OK.