Feature space visualization tool + side by side gifs visual #29
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gallettilance
requested changes
Nov 19, 2024
kviz/visualizer.py
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| @@ -416,6 +417,146 @@ def view_activations_for(self, X, filename='activations', duration=1000, x_color | |||
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| self._stack_gifs(network_images, input_images, filename, duration) | |||
| return | |||
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I was thinking the logic would involve matplotlib subplots and not combining gifs. Any reason not to do that?
kviz/visualizer.py
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| plt.close() | ||
| return np.asarray(im.open(filename + '.png')) | ||
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| def fit_in_feature_space(self, X, Y, snap_freq = 10, filename='feature_space', duration=1000, **kwargs): |
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I would like this to be an optional flag to the existing fit api and not a whole new api.
SunehB
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gallettilance
requested changes
Nov 29, 2024
| @@ -19,7 +19,7 @@ | |||
| 'networkx', | |||
| 'pygraphviz', | |||
| 'matplotlib', | |||
| 'imageio' | |||
| @@ -3,6 +3,8 @@ | |||
| from tensorflow.keras import layers | |||
| import sklearn.datasets as datasets | |||
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| @@ -71,3 +73,18 @@ def test_regression(): | |||
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| dg = Visualizer(model) | |||
| dg.fit(X, Y, 100, 'test_regression', 100, epochs=10000, verbose=0, batch_size=200) | |||
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need an extra line here between functions
| @@ -436,7 +509,6 @@ def view_activations_for(self, X, filename='activations', duration=1000, x_color | |||
| self._stack_gifs(network_images, input_images, filename, duration) | |||
| return | |||
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| axes[1].imshow(self._snap_feature_space(X, Y, filename)) | ||
| axes[1].axis('off') | ||
| axes[1].set_title("Feature Space") |
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Suggested change
| axes[1].set_title("Feature Space") | |
| axes[1].set_title("Feature Space At Hidden Layer 1") |
| @@ -350,9 +396,36 @@ def fit(self, X, Y, snap_freq=10, filename='decision_boundary', duration=1000, * | |||
| else: | |||
| epochs = snap_freq | |||
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| for _ in range(int(epochs / snap_freq)): | |||
| temp_dir = "snapshots" | |||
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please remove this directory after the gifs are created
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also make this a hidden directory with a . prefix
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| fig, axes = plt.subplots(1, 2, figsize=(12, 6)) | ||
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| axes[0].imshow(self._snap_decision_boundary(X, Y, filename)) | ||
| axes[0].axis('off') | ||
| axes[0].set_title("Input Space") | ||
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| axes[1].imshow(self._snap_feature_space(X, Y, filename)) | ||
| axes[1].axis('off') | ||
| axes[1].set_title("Feature Space") | ||
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| temp_filename = os.path.join(temp_dir, f"epoch_{epoch}.png") |
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ALl this should move inside snap_feature_space
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Description of the change:
Added functions fit_in_feature_space and _snap_feature_space in visualizer.py to visualize the learned decision boundary in the feature space
Added function combine_gifs to visualize the learned decision boundary gifs side by side
Added test_feature_space in test_visualizer.py
Motivation for the change:
We wanted a way to visualize gifs side by side
Visualizing the decision boundary in the feature space can show how the network transforms data to make it linearly separable
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