visualizer
- visualizer class¶
The file yann.modules.visualizer.py
contains the definition for the visualizer:
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yann.modules.visualizer.
save_images
(imgs, prefix, is_color, verbose=2)[source]¶ This functions produces a visualiation of the filters.
Parameters: - imgs – images of shape .. [num_imgs, height, width, channels] Note the change in order. it can also be in lots of other shapes and they will be reshaped and saved as images.
- prefix – address to save the image to
- is_color – If the image is color or not. True only if image shape is of color images.
- verbose – As Always
-
class
yann.modules.visualizer.
visualizer
(visualizer_init_args, verbose=2)[source]¶ Visualizer saves down images to visualize. The initilizer only initializes the directories for storing visuals. Three types of visualizations are saved down:
- filters of each layer
- activations of each layer
- raw images to check the activations against
Parameters: - verbose – Similar to any 3-level verbose in the toolbox.
- visualizer_init_args –
visualer_params
is a dictionary of the form:visualizer_init_args = { "root" : <location to save the visualizations at>, "frequency" : <integer>, after how many epochs do you need to visualize. Default value is 1 "sample_size": <integer, prefer squares>, simply save down random images from the datasets saves down activations for the same images also. Default value is 16 "rgb_filters": <bool> flag. if True a 3D-RGB rendition of the CNN filters is rendered. Default value is False. "debug_functions" : <bool> visualize train and test and other theano functions. default is False. Needs pydot and dv2viz to be installed. "debug_layers" : <bool> Will print layer activities from input to that layer output. ( this is almost always useless because test debug function will combine all these layers and print directly.) "id" : id of the visualizer }
Returns: A visualizer object.
Return type: -
initialize
(batch_size, verbose=2)[source]¶ Function that cooks the visualizer for some dataset.
Parameters: - batch_size – form dataset
- verbose – as always
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theano_function_visualizer
(function, short_variable_names=False, format='pdf', verbose=2)[source]¶ This basically prints a visualization of any theano function using the in-built theano visualizer. It will save both a interactive html file and a plain old png file. This is just a wrapper to theano’s visualization tools.
Parameters: - function – theano function to print
- short_variable_names – If True will print variables in short.
- format – Any pydot supported format. Default is ‘pdf’
- verbose – As usual.
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visualize_activities
(layer_activities, epoch, index=0, verbose=2)[source]¶ This method saves down all activities.
Parameters: - layer_activities – network’s layer_activities as created
- epoch – what epoch are we running currently.
- verbose – as always