diff --git a/README.rst b/README.rst
index d8d23294ec3a0..503f350bbb537 100644
--- a/README.rst
+++ b/README.rst
@@ -1,33 +1,38 @@
.. image:: https://github.com/unifyai/unifyai.github.io/blob/master/img/externally_linked/logo.png?raw=true
:width: 100%
+ :class: only-light
+
+.. image:: https://github.com/unifyai/unifyai.github.io/blob/master/img/externally_linked/logo_dark.png?raw=true
+ :width: 100%
+ :class: only-dark
.. raw:: html
@@ -37,23 +42,23 @@
.. raw:: html
diff --git a/docs/partial_source/deep_dive/function_types.rst b/docs/partial_source/deep_dive/function_types.rst
index b56f20d41b947..3097bc60b4cd1 100644
--- a/docs/partial_source/deep_dive/function_types.rst
+++ b/docs/partial_source/deep_dive/function_types.rst
@@ -37,6 +37,7 @@ These four function categorizations are all **mutually exclusive**, and combined
.. image:: https://github.com/unifyai/unifyai.github.io/blob/master/img/externally_linked/deep_dive/function_types/four_function_types.png?raw=true
:align: center
:width: 50%
+ :class: dark-light
Primary Functions
-----------------
@@ -143,6 +144,7 @@ This categorization is **not** mutually exclusive, as outlined by the Venn diagr
.. image:: https://github.com/unifyai/unifyai.github.io/blob/master/img/externally_linked/deep_dive/function_types/nestable.png?raw=true
:align: center
:width: 50%
+ :class: dark-light
The *nestable* property makes it very easy to write a single piece of code that can deal either with individual arguments or arbitrary batches of nested arguments.
This is very useful in machine learning, where batches of different training data often need to be processed concurrently.
@@ -170,6 +172,7 @@ This is another categorization which is **not** mutually exclusive, as outlined
.. image:: https://github.com/unifyai/unifyai.github.io/blob/master/img/externally_linked/deep_dive/function_types/convenience.png?raw=true
:align: center
:width: 50%
+ :class: dark-light
Primary convenience functions include: `ivy.can_cast`_ which determines if one data type can be cast to another data type according to type-promotion rules, `ivy.dtype`_ which gets the data type for the input array, and `ivy.dev`_ which gets the device for the input array.
diff --git a/docs/partial_source/deep_dive/ivy_tests.rst b/docs/partial_source/deep_dive/ivy_tests.rst
index ceafec0992990..2421bf0582fae 100644
--- a/docs/partial_source/deep_dive/ivy_tests.rst
+++ b/docs/partial_source/deep_dive/ivy_tests.rst
@@ -74,6 +74,7 @@ Testing Pipeline
.. image:: https://github.com/unifyai/unifyai.github.io/blob/master/img/externally_linked/deep_dive/ivy_tests/testing_pipeline.png?raw=true
:align: center
:width: 100%
+ :class: dark-light
*An abstract look at Ivy testing cycle.*
1. **Test Data Generation**: At this stage, we generate our test data for the testing function, using `Hypothesis`_ and `test helpers`_ strategies.
diff --git a/docs/partial_source/index_prepend.rst b/docs/partial_source/index_prepend.rst
index 8219c8d4e00f0..2b0c5c9d3d02b 100644
--- a/docs/partial_source/index_prepend.rst
+++ b/docs/partial_source/index_prepend.rst
@@ -1,5 +1,5 @@
.. raw:: html
diff --git a/docs/partial_source/related_work/exchange_formats.rst b/docs/partial_source/related_work/exchange_formats.rst
index 1989a89d1042d..4378e5303d5f4 100644
--- a/docs/partial_source/related_work/exchange_formats.rst
+++ b/docs/partial_source/related_work/exchange_formats.rst
@@ -15,10 +15,13 @@ Exchange Formats
.. |onnx| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/exchange_formats/onnx.png
:height: 20pt
+ :class: dark-light
.. |nnef| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/exchange_formats/nnef.png
:height: 15pt
+ :class: dark-light
.. |coreml| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/exchange_formats/coreml.png
:height: 20pt
+ :class: dark-light
Neural network exchange formats define a standardized file representation specifically for neural networks.
The idea is that these can be used as an intermediate representation for communicating or “exchanging” neural network architectures between different ML frameworks or between ML frameworks and the target hardware.
diff --git a/docs/partial_source/related_work/frameworks.rst b/docs/partial_source/related_work/frameworks.rst
index 1c8415c9787d0..8620690b38d7b 100644
--- a/docs/partial_source/related_work/frameworks.rst
+++ b/docs/partial_source/related_work/frameworks.rst
@@ -54,42 +54,61 @@ Frameworks
.. |matlab| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/matlab.png
:height: 20pt
+ :class: dark-light
.. |scipy| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/scipy.png
:height: 20pt
+ :class: dark-light
.. |torch| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/torch.png
:height: 20pt
+ :class: dark-light
.. |numpy| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/numpy.png
:height: 20pt
+ :class: dark-light
.. |scikit-learn| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/scikit-learn.png
:height: 15pt
+ :class: dark-light
.. |theano| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/theano.png
:height: 10pt
+ :class: dark-light
.. |pandas| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/pandas.png
:height: 22pt
+ :class: dark-light
.. |julia| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/julia.png
:height: 20pt
+ :class: dark-light
.. |apache-spark-mllib| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/apache-spark-mllib.png
:height: 20pt
+ :class: dark-light
.. |caffe| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/caffe.png
:height: 10pt
+ :class: dark-light
.. |chainer| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/chainer.png
:height: 20pt
+ :class: dark-light
.. |tensorflow-1| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/tensorflow-1.png
:height: 20pt
+ :class: dark-light
.. |mxnet| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/mxnet.png
:height: 20pt
+ :class: dark-light
.. |cntk| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/cntk.png
:height: 20pt
+ :class: dark-light
.. |pytorch| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/pytorch.png
:height: 22pt
+ :class: dark-light
.. |flux| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/flux.png
:height: 22pt
+ :class: dark-light
.. |jax| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/jax.png
:height: 20pt
+ :class: dark-light
.. |tensorflow-2| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/tensorflow-2.png
:height: 20pt
+ :class: dark-light
.. |dex-language| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/frameworks/dex-language.png
:height: 20pt
+ :class: dark-light
Here we list some of the most prominent frameworks for array computation.
These are the individual frameworks which the wrapper frameworks mentioned above generally wrap around and abstract.
diff --git a/docs/partial_source/related_work/vendor_specific_apis.rst b/docs/partial_source/related_work/vendor_specific_apis.rst
index 1db4c7d611e8b..3329dd2a35d32 100644
--- a/docs/partial_source/related_work/vendor_specific_apis.rst
+++ b/docs/partial_source/related_work/vendor_specific_apis.rst
@@ -15,8 +15,10 @@ Vendor-Specific APIs
.. |tensorrt| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/vendor_specific_apis/tensorrt.png
:height: 15pt
+ :class: dark-light
.. |cuda| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/vendor_specific_apis/cuda.png
:height: 20pt
+ :class: dark-light
Vendor-specific APIs provide an interface to define customized operations for hardware from specific vendors.
The libraries are written exclusively for hardware from this vendor, and so the code is clearly not generalized nor is it intended to be.
diff --git a/docs/partial_source/related_work/wrapper_frameworks.rst b/docs/partial_source/related_work/wrapper_frameworks.rst
index 45d29e407f315..028d1398d5e8e 100644
--- a/docs/partial_source/related_work/wrapper_frameworks.rst
+++ b/docs/partial_source/related_work/wrapper_frameworks.rst
@@ -25,8 +25,10 @@ Wrapper Frameworks
.. |eagerpy| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/wrapper_frameworks/eagerpy.png
:height: 15pt
+ :class: dark-light
.. |keras| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/wrapper_frameworks/keras.png
:height: 20pt
+ :class: dark-light
.. |thinc| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/wrapper_frameworks/thinc.png
:height: 15pt
.. |tensorly| image:: https://raw.githubusercontent.com/unifyai/unifyai.github.io/master/img/externally_linked/related_work/wrapper_frameworks/tensorly.png