DOCS: Fixed links to TF docs + added link to online MLI documentation into the main readme

Author: dzakhar

README.md

@@ -2,7 +2,7 @@ embARC Machine Learning Inference Library
 ==================================================
 
 This repository contains source code of embARC Machine Learning Inference Library (embARC MLI Library),
-examples and documentation.
+examples and documentation sources. Full documentation is available [online](https://embarc.org/embarc_mli).
 
 ## Release notes
 ----------------

doc/documents/MLI_kernels/convolution_2d.rst

@@ -49,7 +49,7 @@ inputs shape.
 
 For more details on calculations see convolution part of `TensorFlow–Neural Network details`_. 
 
-.. _TensorFlow–Neural Network details: https://www.tensorflow.org/api_guides/python/nn.
+.. _TensorFlow–Neural Network details: https://www.tensorflow.org/versions/r1.11/api_guides/python/nn
 
 ReLU activation function might be applied to result of convolution. The
 following types of ReLU activations are supported (for more info see

doc/documents/MLI_kernels/pooling_max.rst

@@ -34,7 +34,7 @@ padding parameters. This logic is similar to convolution 2D operation
 For more information on calculations, see the pooling part of
 `TensorFlow–Neural Network details`_.
 
-.. _TensorFlow–Neural Network details: https://www.tensorflow.org/api_guides/python/nn   
+.. _TensorFlow–Neural Network details: https://www.tensorflow.org/versions/r1.11/api_guides/python/nn   
 
 .. caution::
    Ensure that input and output

doc/documents/library_model/functions.rst

@@ -137,8 +137,8 @@ Naming convention for the specializations: \
    |                       | parameters to achieve     |                       |
    |                       | same output size          |                       |
    |                       | (similar to ‘SAME’        |                       |
-   |                       | padding scheme used       |                       |
-   |                       | in TensorFlow [3])        |                       |
+   |                       | `padding scheme`_ used    |                       |
+   |                       | in TensorFlow)            |                       |
    +-----------------------+---------------------------+-----------------------+
    | ``Input channels``    | [_ch\ *n*]                | convolution group,    |
    |                       |                           | pooling group         |
@@ -182,6 +182,9 @@ Naming convention for the specializations: \
    |                       | specializations.          |                       |
    +-----------------------+---------------------------+-----------------------+
 
+.. _padding scheme: https://www.tensorflow.org/versions/r1.11/api_guides/python/nn#Notes_on_SAME_Convolution_Padding
+
+
 
 For example, the function name of a 16bit 2d convolution kernel with
 CHW layout and a kernel size of 3x3 and stride of 1 is:

doc/documents/library_model/hw_dependencies_config.rst

@@ -109,7 +109,7 @@ round to the nearest even). All parameters are described in *MetaWare
 Fixed-Point Reference for ARC EM and ARC HS*.
 
 .. note::
-   The MLI Library sets the required DSP mode inside each function where it is needed, but does not restore it to previous state. If another ARC DSP code beside MLI library is used in an application, ensure that you set the required DSP mode before its execution. For more information see  “Configuring the ARC DSP Extensions” section of *MetaWare DSP Programming Guide for ARC EM and ARC HS* or “Using the FXAPI” section of entry [5] of *MetaWare Fixed-Point Reference for ARC EM and ARC HS*.
+   The MLI Library sets the required DSP mode inside each function where it is needed, but does not restore it to previous state. If another ARC DSP code beside MLI library is used in an application, ensure that you set the required DSP mode before its execution. For more information see  “Configuring the ARC DSP Extensions” section of *MetaWare DSP Programming Guide for ARC EM and ARC HS* or “Using the FXAPI” section of *MetaWare Fixed-Point Reference for ARC EM and ARC HS*.
 
 AGU Support
 ^^^^^^^^^^^