Docs redesigning inference section 25.1 (#29566)

port:
#29298
#29565

---------

Signed-off-by: sgolebiewski-intel <sebastianx.golebiewski@intel.com>
Co-authored-by: sgolebiewski-intel <sebastianx.golebiewski@intel.com>

Author: kblaszczak-intel

docs/articles_en/about-openvino/performance-benchmarks/getting-performance-numbers.rst

@@ -132,7 +132,7 @@ General considerations
    * Do not include model loading time.
    * Ensure that the inputs are identical for OpenVINO Runtime and the framework. For example, watch out for random values that can be used to populate the inputs.
    * In situations when any user-side pre-processing should be tracked separately, consider :doc:`image pre-processing and conversion <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>`.
-   * When applicable, leverage the :doc:`Dynamic Shapes support <../../openvino-workflow/running-inference/dynamic-shapes>`.
+   * When applicable, leverage the :doc:`Dynamic Shapes support <../../openvino-workflow/running-inference/model-input-output/dynamic-shapes>`.
    * If possible, demand the same accuracy. For example, TensorFlow allows ``FP16`` execution, so when comparing to that, make sure to test the OpenVINO Runtime with the ``FP16`` as well.
 
 .. dropdown:: Make sure the benchmarking setup is proper for the selected scenario
@@ -244,7 +244,7 @@ request, while the actual latency can be quite different.
 
 Lastly, the performance statistics with both performance counters and execution graphs are
 averaged, so such data for the
-:doc:`inputs of dynamic shapes <../../openvino-workflow/running-inference/dynamic-shapes>`
+:doc:`inputs of dynamic shapes <../../openvino-workflow/running-inference/model-input-output/dynamic-shapes>`
 should be measured carefully, preferably by isolating the specific shape and executing multiple
 times in a loop, to gather reliable data.
 

docs/articles_en/documentation/compatibility-and-support/supported-devices.rst

@@ -42,9 +42,9 @@ Feature Support and API Coverage
  :doc:`Automatic batching <../../openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching>`                     No      Yes        No
  :doc:`Multi-stream execution <../../openvino-workflow/running-inference/optimize-inference/optimizing-throughput>`                       Yes     Yes        No
  :doc:`Model caching <../../openvino-workflow/running-inference/optimize-inference/optimizing-latency/model-caching-overview>`            Yes     Partial    Yes
- :doc:`Dynamic shapes <../../openvino-workflow/running-inference/dynamic-shapes>`                                                         Yes     Partial    No
+ :doc:`Dynamic shapes <../../openvino-workflow/running-inference/model-input-output/dynamic-shapes>`                                      Yes     Partial    No
  :doc:`Preprocessing acceleration <../../openvino-workflow/running-inference/optimize-inference/optimize-preprocessing>`                  Yes     Yes        No
- :doc:`Stateful models <../../openvino-workflow/running-inference/stateful-models>`                                                       Yes     Yes        Yes
+ :doc:`Stateful models <../../openvino-workflow/running-inference/inference-request/stateful-models>`                                     Yes     Yes        Yes
  :doc:`Extensibility <../../documentation/openvino-extensibility>`                                                                        Yes     Yes        No
 ======================================================================================================================================== ======= ========== ===========
 
@@ -73,7 +73,7 @@ Feature Support and API Coverage
 +-------------------------+-----------+------------------+-------------------+
 
 For setting up a relevant configuration, refer to the
-:doc:`Integrate with Customer Application <../../openvino-workflow/running-inference/integrate-openvino-with-your-application>`
+:doc:`Integrate with Customer Application <../../openvino-workflow/running-inference>`
 topic (step 3 "Configure input and output").
 
 .. dropdown:: Device support across OpenVINO 2024.6 distributions

docs/articles_en/documentation/openvino-extensibility/transformation-api.rst

@@ -25,7 +25,7 @@ Working with Model
 ##################
 
 Before moving to the transformation part, it is important to say a few words about the functions which allow modifying ``ov::Model``.
-This section extends the :doc:`model representation guide <../../openvino-workflow/running-inference/integrate-openvino-with-your-application/model-representation>`
+This section extends the :doc:`model representation guide <../../openvino-workflow/running-inference/model-representation>`
 and introduces an API for ``ov::Model`` manipulation.
 
 Working with node input and output ports
@@ -244,6 +244,6 @@ additional debug capabilities by using the following environment variables:
 See Also
 ########
 
-* :doc:`OpenVINO™ Model Representation <../../openvino-workflow/running-inference/integrate-openvino-with-your-application/model-representation>`
+* :doc:`OpenVINO™ Model Representation <../../openvino-workflow/running-inference/model-representation>`
 * :doc:`OpenVINO™ Extensions <../openvino-extensibility>`
 

docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/infrastructure/assign-6.rst

@@ -16,7 +16,7 @@ Assign
 
 ReadValue, Assign, and Variable define a coherent mechanism for reading, writing and
 storing a memory buffer between inference calls. More details can be found on the
-:doc:`State API <../../../../../../openvino-workflow/running-inference/stateful-models>` documentation page.
+:doc:`State API <../../../../../../openvino-workflow/running-inference/inference-request/stateful-models>` documentation page.
 
 *Assign* sets an input value to the ``variable_id`` variable. This value will be read
 by the *ReadValue* operation on the next inference call if it has not been reset.

docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/infrastructure/read-value-6.rst

@@ -17,7 +17,7 @@ ReadValue
 
 *ReadValue*, *Assign*, and *Variable* define a coherent mechanism for reading, writing,
 and storing some memory buffer between inference calls. More details can be found on the
-:doc:`StateAPI <../../../../../../openvino-workflow/running-inference/stateful-models>` documentation page.
+:doc:`StateAPI <../../../../../../openvino-workflow/running-inference/inference-request/stateful-models>` documentation page.
 
 If the 1st input is provided and this is the first inference or reset has been called,
 *ReadValue* returns the value from the 1st input.

docs/articles_en/documentation/openvino-ir-format/operation-sets/operation-specs/movement/unique-10.rst

@@ -52,7 +52,7 @@ The operator can either work in elementwise mode searching for unique values in
 
 **Outputs**
 
-* **1**: The output tensor containing unique elements (individual values or subtensors). This tensor's type matches the type of the first input tensor: *T*. The values in this tensor are either sorted ascendingly or maintain the same order as in the input tensor. The shape of this output depends on the values of the input tensor and will very often be dynamic. Please refer to the article describing how :doc:`Dynamic Shapes <../../../../../openvino-workflow/running-inference/dynamic-shapes>` are handled in OpenVINO.
+* **1**: The output tensor containing unique elements (individual values or subtensors). This tensor's type matches the type of the first input tensor: *T*. The values in this tensor are either sorted ascendingly or maintain the same order as in the input tensor. The shape of this output depends on the values of the input tensor and will very often be dynamic. Please refer to the article describing how :doc:`Dynamic Shapes <../../../../../openvino-workflow/running-inference/model-input-output/dynamic-shapes>` are handled in OpenVINO.
 * **2**: The output tensor containing indices of the locations of unique elements. The indices map the elements in the first output tensor to their locations in the input tensor. The index always points to the first occurrence of a given unique output element in the input tensor. This is a 1D tensor with type controlled by the ``index_element_type`` attribute.
 * **3**: The output tensor containing indices of the locations of elements of the input tensor in the first output tensor. This means that for each element of the input tensor this output will point to the unique value in the first output tensor of this operator. This is a 1D tensor with type controlled by the ``index_element_type`` attribute.
 * **4**: The output tensor containing the number of occurrences of each unique value produced by this operator in the first output tensor. This is a 1D tensor with type controlled by the ``count_element_type`` attribute.

docs/articles_en/get-started.rst

@@ -90,7 +90,7 @@ View :doc:`sample code <get-started/learn-openvino/openvino-samples>` for variou
 Integrate OpenVINO With Your Application
 ----------------------------------------
 
-Learn how to :doc:`use the OpenVINO API to implement an inference pipeline <openvino-workflow/running-inference/integrate-openvino-with-your-application>` in your application.
+Learn how to :doc:`use the OpenVINO API to implement an inference pipeline <openvino-workflow/running-inference>` in your application.
 
 .. _openvino-advanced-features:
 
@@ -123,7 +123,7 @@ Pipeline and model configuration features in OpenVINO Runtime allow you to easil
 
 * :doc:`Automatic Batching <openvino-workflow/running-inference/inference-devices-and-modes/automatic-batching>` performs on-the-fly grouping of inference requests to maximize utilization of the target hardware’s memory and processing cores.
 * :doc:`Performance Hints <openvino-workflow/running-inference/optimize-inference/high-level-performance-hints>` automatically adjust runtime parameters to prioritize for low latency or high throughput
-* :doc:`Dynamic Shapes <openvino-workflow/running-inference/dynamic-shapes>` reshapes models to accept arbitrarily-sized inputs, increasing flexibility for applications that encounter different data shapes
+* :doc:`Dynamic Shapes <openvino-workflow/running-inference/model-input-output/dynamic-shapes>` reshapes models to accept arbitrarily-sized inputs, increasing flexibility for applications that encounter different data shapes
 * :doc:`Benchmark Tool <get-started/learn-openvino/openvino-samples/benchmark-tool>` characterizes model performance in various hardware and pipeline configurations
 
 .. _additional-about-openvino/additional-resources:

docs/articles_en/get-started/install-openvino/install-openvino-archive-macos.rst

@@ -188,6 +188,6 @@ Additional Resources
 
 * :doc:`Troubleshooting Guide for OpenVINO Installation & Configuration <../install-openvino>`
 * :doc:`Convert models for use with OpenVINO™ <../../../openvino-workflow/model-preparation/convert-model-to-ir>`
-* :doc:`Write your own OpenVINO™ applications <../../../openvino-workflow/running-inference/integrate-openvino-with-your-application>`
+* :doc:`Write your own OpenVINO™ applications <../../../openvino-workflow/running-inference>`
 * Sample applications: :doc:`OpenVINO™ Toolkit Samples Overview <../../../get-started/learn-openvino/openvino-samples>`
 * Pre-trained deep learning models on `Hugging Face <https://huggingface.co/OpenVINO>`__

docs/articles_en/get-started/install-openvino/install-openvino-archive-windows.rst

@@ -211,6 +211,6 @@ Additional Resources
 
 * :doc:`Troubleshooting Guide for OpenVINO Installation & Configuration <../install-openvino>`
 * :doc:`Convert models for use with OpenVINO™ <../../../openvino-workflow/model-preparation/convert-model-to-ir>`
-* :doc:`Write your own OpenVINO™ applications <../../../openvino-workflow/running-inference/integrate-openvino-with-your-application>`
+* :doc:`Write your own OpenVINO™ applications <../../../openvino-workflow/running-inference>`
 * Sample applications: :doc:`OpenVINO™ Toolkit Samples Overview <../../../get-started/learn-openvino/openvino-samples>`
 * Pre-trained deep learning models on `Hugging Face <https://huggingface.co/OpenVINO>`__.

docs/articles_en/get-started/learn-openvino/openvino-samples/bert-benchmark.rst

@@ -26,7 +26,7 @@ resulting model, downloads a dataset and runs a benchmark on the dataset.
 
 
 You can see the explicit description of each sample step at
-:doc:`Integration Steps <../../../openvino-workflow/running-inference/integrate-openvino-with-your-application>`
+:doc:`Integration Steps <../../../openvino-workflow/running-inference>`
 section of "Integrate OpenVINO™ Runtime with Your Application" guide.
 
 Running
@@ -60,7 +60,7 @@ The sample outputs how long it takes to process a dataset.
 Additional Resources
 ####################
 
-- :doc:`Integrate the OpenVINO™ Runtime with Your Application <../../../openvino-workflow/running-inference/integrate-openvino-with-your-application>`
+- :doc:`Integrate the OpenVINO™ Runtime with Your Application <../../../openvino-workflow/running-inference>`
 - :doc:`Get Started with Samples <get-started-demos>`
 - :doc:`Using OpenVINO Samples <../openvino-samples>`
 - :doc:`Convert a Model <../../../openvino-workflow/model-preparation/convert-model-to-ir>`