dianna-ai · loostrum · Mar 20, 2024 · Jan 26, 2024 · Jan 26, 2024 · Jan 26, 2024
diff --git a/dianna/dashboard/_movie_model.py b/dianna/dashboard/_movie_model.py
@@ -1,6 +1,6 @@
 import os
 import numpy as np
-from _shared import data_directory
+from _shared import label_directory
 from scipy.special import expit as sigmoid
 from torchtext.vocab import Vectors
 from dianna import utils
@@ -13,7 +13,7 @@ class MovieReviewsModelRunner:
     def __init__(self, model, word_vectors=None, max_filter_size=5):
         """Initializes the class."""
         if word_vectors is None:
-            word_vectors = data_directory / 'movie_reviews_word_vectors.txt'
+            word_vectors = label_directory / 'movie_reviews_word_vectors.txt'
 
         self.run_model = utils.get_function(model)
         self.vocab = Vectors(word_vectors, cache=os.path.dirname(word_vectors))

diff --git a/dianna/dashboard/_shared.py b/dianna/dashboard/_shared.py
@@ -12,7 +12,8 @@
     from importlib.resources import files
 
 data_directory = files('dianna.data')
-
+model_directory = files('dianna.models')
+label_directory = files('dianna.labels')
 
 @st.cache_data
 def get_base64_of_bin_file(png_file):

diff --git a/dianna/dashboard/pages/1_Images.py b/dianna/dashboard/pages/1_Images.py
@@ -9,6 +9,8 @@
 from _shared import _methods_checkboxes
 from _shared import add_sidebar_logo
 from _shared import data_directory
+from _shared import label_directory
+from _shared import model_directory
 from dianna.visualization import plot_image
 
 add_sidebar_logo()
@@ -37,8 +39,8 @@
 
 if load_example:
     image_file = (data_directory / 'digit0.png')
-    image_model_file = (data_directory / 'mnist_model_tf.onnx')
-    image_label_file = (data_directory / 'labels_mnist.txt')
+    image_model_file = (model_directory / 'mnist_model_tf.onnx')
+    image_label_file = (label_directory / 'labels_mnist.txt')
 
 if not (image_file and image_model_file and image_label_file):
     st.info('Add your input data in the left panel to continue')

diff --git a/dianna/dashboard/pages/2_Text.py b/dianna/dashboard/pages/2_Text.py
@@ -8,7 +8,8 @@
 from _shared import _get_top_indices_and_labels
 from _shared import _methods_checkboxes
 from _shared import add_sidebar_logo
-from _shared import data_directory
+from _shared import label_directory
+from _shared import model_directory
 from _text_utils import format_word_importances
 
 add_sidebar_logo()
@@ -35,8 +36,8 @@
 
 if load_example:
     text_input = 'The movie started out great but the ending was dissappointing'
-    text_model_file = data_directory / 'movie_review_model.onnx'
-    text_label_file = data_directory / 'labels_text.txt'
+    text_model_file = model_directory / 'movie_review_model.onnx'
+    text_label_file = label_directory / 'labels_text.txt'
 
 if not (text_input and text_model_file and text_label_file):
     st.info('Add your input data in the left panel to continue')

diff --git a/dianna/dashboard/pages/3_Time_series.py b/dianna/dashboard/pages/3_Time_series.py
@@ -8,6 +8,8 @@
 from _shared import _methods_checkboxes
 from _shared import add_sidebar_logo
 from _shared import data_directory
+from _shared import label_directory
+from _shared import model_directory
 from _ts_utils import _convert_to_segments
 from _ts_utils import open_timeseries
 from dianna.visualization import plot_timeseries
@@ -34,9 +36,9 @@
 
 if load_example:
     ts_file = (data_directory / 'weather_data.npy')
-    ts_model_file = (data_directory /
+    ts_model_file = (model_directory /
                      'season_prediction_model_temp_max_binary.onnx')
-    ts_label_file = (data_directory / 'weather_data_labels.txt')
+    ts_label_file = (label_directory / 'weather_data_labels.txt')
 
 if not (ts_file and ts_model_file and ts_label_file):
     st.info('Add your input data in the left panel to continue')

diff --git a/tutorials/img/bee.jpg → dianna/data/bee.jpg b/tutorials/img/bee.jpg → dianna/data/bee.jpg
diff --git a/dianna/data/bee_2.png b/dianna/data/bee_2.png
diff --git a/...als/data/leafsnap_example_acer_rubrum.jpg → dianna/data/leafsnap_example_acer_rubrum.jpg b/...als/data/leafsnap_example_acer_rubrum.jpg → dianna/data/leafsnap_example_acer_rubrum.jpg
diff --git a/tutorials/data/shapes.npz → dianna/data/shapes.npz b/tutorials/data/shapes.npz → dianna/data/shapes.npz
diff --git a/tutorials/data/coffee_test.csv → dianna/labels/coffee_test.csv b/tutorials/data/coffee_test.csv → dianna/labels/coffee_test.csv
diff --git a/tutorials/data/coffee_train.csv → dianna/labels/coffee_train.csv b/tutorials/data/coffee_train.csv → dianna/labels/coffee_train.csv
diff --git a/dianna/data/labels_mnist.txt → dianna/labels/labels_mnist.txt b/dianna/data/labels_mnist.txt → dianna/labels/labels_mnist.txt
diff --git a/dianna/data/labels_resnet50.txt → dianna/labels/labels_resnet50.txt b/dianna/data/labels_resnet50.txt → dianna/labels/labels_resnet50.txt
diff --git a/dianna/data/labels_text.txt → dianna/labels/labels_text.txt b/dianna/data/labels_text.txt → dianna/labels/labels_text.txt
diff --git a/tutorials/data/leafsnap_classes.csv → dianna/labels/leafsnap_classes.csv b/tutorials/data/leafsnap_classes.csv → dianna/labels/leafsnap_classes.csv
diff --git a/dianna/data/movie_reviews_word_vectors.txt → dianna/labels/movie_reviews_word_vectors.txt b/dianna/data/movie_reviews_word_vectors.txt → dianna/labels/movie_reviews_word_vectors.txt
diff --git a/dianna/data/weather_data_labels.txt → dianna/labels/weather_data_labels.txt b/dianna/data/weather_data_labels.txt → dianna/labels/weather_data_labels.txt
diff --git a/tutorials/models/coffee.onnx → dianna/models/coffee.onnx b/tutorials/models/coffee.onnx → dianna/models/coffee.onnx
diff --git a/tutorials/models/geometric_shapes_model.onnx → dianna/models/geometric_shapes_model.onnx b/tutorials/models/geometric_shapes_model.onnx → dianna/models/geometric_shapes_model.onnx
diff --git a/dianna/data/leafsnap_model.onnx → dianna/models/leafsnap_model.onnx b/dianna/data/leafsnap_model.onnx → dianna/models/leafsnap_model.onnx
diff --git a/tutorials/models/mnist_model.onnx → dianna/models/mnist_model.onnx b/tutorials/models/mnist_model.onnx → dianna/models/mnist_model.onnx
diff --git a/dianna/data/mnist_model_tf.onnx → dianna/models/mnist_model_tf.onnx b/dianna/data/mnist_model_tf.onnx → dianna/models/mnist_model_tf.onnx
diff --git a/dianna/data/movie_review_model.onnx → dianna/models/movie_review_model.onnx b/dianna/data/movie_review_model.onnx → dianna/models/movie_review_model.onnx
diff --git a/tutorials/models/penguin_model.onnx → dianna/models/penguin_model.onnx b/tutorials/models/penguin_model.onnx → dianna/models/penguin_model.onnx
diff --git a/...son_prediction_model_temp_max_binary.onnx → ...son_prediction_model_temp_max_binary.onnx b/...son_prediction_model_temp_max_binary.onnx → ...son_prediction_model_temp_max_binary.onnx
diff --git a/...dels/sunshine_hours_regression_model.onnx → ...dels/sunshine_hours_regression_model.onnx b/...dels/sunshine_hours_regression_model.onnx → ...dels/sunshine_hours_regression_model.onnx
diff --git a/docs/tutorials/kernel_mnist.nblink b/docs/tutorials/kernel_mnist.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/kernelshap_mnist.ipynb"
-}
+    "path": "../../tutorials/explainers/KernelSHAP/kernelshap_mnist.ipynb"
+}
diff --git a/docs/tutorials/kernelshap_geometric_shapes.nblink b/docs/tutorials/kernelshap_geometric_shapes.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/kernelshap_geometric_shapes.ipynb"
-}
+    "path": "../../tutorials/explainers/KernelSHAP/kernelshap_geometric_shapes.ipynb"
+}
diff --git a/docs/tutorials/lime_images.nblink b/docs/tutorials/lime_images.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/lime_images.ipynb"
-}
+    "path": "../../tutorials/explainers/LIME/lime_images.ipynb"
+}
diff --git a/docs/tutorials/lime_text.nblink b/docs/tutorials/lime_text.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/lime_text.ipynb"
-}
+    "path": "../../tutorials/explainers/LIME/lime_text.ipynb"
+}
diff --git a/docs/tutorials/rise_imagenet.nblink b/docs/tutorials/rise_imagenet.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/rise_imagenet.ipynb"
-}
+    "path": "../../tutorials/explainers/RISE/rise_imagenet.ipynb"
+}
diff --git a/docs/tutorials/rise_mnist.nblink b/docs/tutorials/rise_mnist.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/rise_mnist.ipynb"
-}
+    "path": "../../tutorials/explainers/RISE/rise_mnist.ipynb"
+}
diff --git a/docs/tutorials/rise_text.nblink b/docs/tutorials/rise_text.nblink
@@ -1,3 +1,3 @@
 {
-    "path": "../../tutorials/rise_text.ipynb"
-}
+    "path": "../../tutorials/explainers/RISE/rise_text.ipynb"
+}
diff --git a/tutorials/README.md b/tutorials/README.md
@@ -1,30 +1,32 @@
 <img width="150" alt="Logo_ER10" src="https://user-images.githubusercontent.com/3244249/151994514-b584b984-a148-4ade-80ee-0f88b0aefa45.png">
 
 ## Tutorials
-This folder contains DIANNA tutorial notebooks. 
+This folder contains DIANNA tutorial notebooks.
 
 To install the dependencies for the tutorials, run
 ```
 pip install .[notebooks]
 ```
 
-For general demonstration of DIANNA click on the logo [<img width="75" alt="Logo_ER10" src="https://user-images.githubusercontent.com/3244249/151994514-b584b984-a148-4ade-80ee-0f88b0aefa45.png">](https://github.com/dianna-ai/dianna/blob/main/tutorials/demo.ipynb) or run it in Colab: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/demo.ipynb).
+For *general demonstration of DIANNA* click on the logo [<img width="75" alt="Logo_ER10" src="https://user-images.githubusercontent.com/3244249/151994514-b584b984-a148-4ade-80ee-0f88b0aefa45.png">](https://github.com/dianna-ai/dianna/blob/main/tutorials/demo.ipynb) or run it in Colab: [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/demo.ipynb).
 
-Click on the XAI method (explainer) names to watch explanatory videos for the respective method.
+For *tutorials on how to convert* an [Keras](https://keras.io/), [PyTorch](https://pytorch.org/), [Scikit-learn](https://scikit-learn.org/stable/) or [Tensorflow](https://www.tensorflow.org/) model to [ONNX](https://onnx.ai/), please see the [conversion tutorials](https://github.com/dianna-ai/dianna/blob/main/tutorials/conversion_onnx/).
 
-Click on the logos below for direct access to a tutorial notebook for an explainability method and data modality/dataset. 
+For *specific XAI methods (explainers)*:
+* Click on the explainer names to watch explanatory videos for the respective method.
+* Click on the logos below for direct access to a tutorial notebook for a combination of explainer and data modality/dataset.
 
-Run the tutorials directly in Google Colab by clicking on the Colab buttons below: 
+Run the tutorials directly in Google Colab by clicking on the Colab buttons below:
 
 |*Modality* \ Method|RISE|[LIME](https://youtu.be/d6j6bofhj2M)|Kernel[SHAP](https://youtu.be/9haIOplEIGM)|
 |:-----|:---|:---|:---|
-|*Images*|[<img width="25" alt="mnist_zero_and_one_half_size" src="https://user-images.githubusercontent.com/3244249/152540187-b7a8239f-6742-437f-8f9b-35b950ce5ddb.png">](rise_mnist.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_mnist.ipynb) | [<img width="20" alt="LeafSnap30 Logo" src="https://user-images.githubusercontent.com/3244249/151539100-dbdfe0f8-485f-45d4-a249-a1f79e970066.png">](lime_images.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_images.ipynb) | [<img width="25" alt="mnist_zero_and_one_half_size" src="https://user-images.githubusercontent.com/3244249/152540187-b7a8239f-6742-437f-8f9b-35b950ce5ddb.png">](kernelshap_mnist.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/kernelshap_mnist.ipynb) |
-| | [<img width="94" alt="ImageNet_autocrop" src="https://user-images.githubusercontent.com/3244249/152542090-fd78fde1-6dec-43b6-a7ae-eea964b8ae28.png">](rise_imagenet.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_imagenet.ipynb) | | [<img width="20" alt="SimpleGeometric Logo" src="https://user-images.githubusercontent.com/3244249/151539027-f2fc3fc0-282a-4993-9680-74ee28bcd360.png">](kernelshap_geometric_shapes.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/kernelshap_geometric_shapes.ipynb)|
-|*Text* |[<img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">](rise_text.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_text.ipynb) |[<img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">](lime_text.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_text.ipynb)  |[]()|
-| *Time series*| [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](rise_timeseries_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/rise_timeseries_weather.ipynb)| [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](lime_timeseries_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_timeseries_weather.ipynb)| |
-| | | [<img width="25" alt="Coffe Logo" src="https://user-images.githubusercontent.com/3244249/241999275-9ab50a0f-5da3-41d2-80e9-70d2c8769162.jpg">](lime_timeseries_coffee.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_timeseries_coffee.ipynb) | |
-| *Tabular* | | [<img width="75" alt="Penguin Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/c7716ad3-f992-4557-80d9-1d8178c7ed57">](lime_tabular_penguin.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_tabular_penguin.ipynb) | |
-| | | [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](lime_tabular_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/lime_tabular_weather.ipynb)| |
+|*Images*|[<img width="25" alt="mnist_zero_and_one_half_size" src="https://user-images.githubusercontent.com/3244249/152540187-b7a8239f-6742-437f-8f9b-35b950ce5ddb.png">](/explainers/RISE/rise_mnist.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/RISE/rise_mnist.ipynb) | [<img width="20" alt="LeafSnap30 Logo" src="https://user-images.githubusercontent.com/3244249/151539100-dbdfe0f8-485f-45d4-a249-a1f79e970066.png">](/explainers/LIME/lime_images.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/LIME/lime_images.ipynb) | [<img width="25" alt="mnist_zero_and_one_half_size" src="https://user-images.githubusercontent.com/3244249/152540187-b7a8239f-6742-437f-8f9b-35b950ce5ddb.png">](/explainers/KernelSHAP/kernelshap_mnist.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/KernelSHAP/kernelshap_mnist.ipynb) |
+| | [<img width="94" alt="ImageNet_autocrop" src="https://user-images.githubusercontent.com/3244249/152542090-fd78fde1-6dec-43b6-a7ae-eea964b8ae28.png">](/explainers/RISE/rise_imagenet.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/RISE/rise_imagenet.ipynb) | | [<img width="20" alt="SimpleGeometric Logo" src="https://user-images.githubusercontent.com/3244249/151539027-f2fc3fc0-282a-4993-9680-74ee28bcd360.png">](/explainers/KernelSHAP/kernelshap_geometric_shapes.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/KernelSHAP/kernelshap_geometric_shapes.ipynb)|
+|*Text* |[<img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">](/explainers/RISE/rise_text.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/RISE/rise_text.ipynb) |[<img width="25" alt="nlp-logo_half_size" src="https://user-images.githubusercontent.com/3244249/152540890-c8e1e37d-f0cc-4f84-80a4-2c59176cbf4c.png">](/explainers/LIME/lime_text.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/LIME/lime_text.ipynb)  |[]()|
+| *Time series*| [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](/explainers/RISE/rise_timeseries_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/RISE/rise_timeseries_weather.ipynb)| [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](/explainers/LIME/lime_timeseries_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/LIME/lime_timeseries_weather.ipynb)| |
+| | | [<img width="25" alt="Coffe Logo" src="https://user-images.githubusercontent.com/3244249/241999275-9ab50a0f-5da3-41d2-80e9-70d2c8769162.jpg">](/explainers/LIME/lime_timeseries_coffee.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/LIME/lime_timeseries_coffee.ipynb) | |
+| *Tabular* | | [<img width="75" alt="Penguin Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/c7716ad3-f992-4557-80d9-1d8178c7ed57">](/explainers/LIME/lime_tabular_penguin.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/LIME/lime_tabular_penguin.ipynb) | |
+| | | [<img width="25" alt="Weather Logo" src="https://user-images.githubusercontent.com/3244249/242001499-3ff3d639-ed2f-4a38-b7ac-957c984bce9f.png">](/explainers/LIME/lime_tabular_weather.ipynb) or [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dianna-ai/dianna/blob/main/tutorials/explainers/LIME/lime_tabular_weather.ipynb)| |
 
 The datasets used in the tutorials are represented with their respective logos:
 |Data modality|Dataset|Logo|
@@ -39,7 +41,4 @@ The datasets used in the tutorials are represented with their respective logos:
 |*Tabular*| [Penguin dataset](https://www.kaggle.com/code/parulpandey/penguin-dataset-the-new-iris)| <img width="75" alt="Penguin Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/c7716ad3-f992-4557-80d9-1d8178c7ed57"> | |
 |           | [Weather dataset](https://zenodo.org/record/7525955) | <img width="25" alt="Weather Logo" src="https://github.com/dianna-ai/dianna/assets/3244249/3ff3d639-ed2f-4a38-b7ac-957c984bce9f">|
 
-The ONNX models used in the tutorials are available at [tutorials/models](https://github.com/dianna-ai/dianna/tree/main/tutorials/models).
-
-
-
+The ONNX models used in the tutorials are available at [dianna/models](https://github.com/dianna-ai/dianna/tree/main/dianna/models).