Fix spelling error ("sprasity" instead of "sparsity")

Thanks to @haim-barad for notifying us about this.

Fix spelling error ("sprasity" instead of "sparsity")
ea173cb9 · Neta Zmora · d1cd450e · ea173cb9 · ea173cb9
Commit ea173cb9 authored 6 years ago by Neta Zmora
--- a/distiller/data_loggers/logger.py
+++ b/distiller/data_loggers/logger.py
@@ -138,7 +138,7 @@ class TensorBoardLogger(DataLogger):
                self.tblogger.scalar_summary('sparsity-2D/weights/' + name,
                                             sparsity_2D(param)*100, epoch)

-        self.tblogger.scalar_summary("sprasity/weights/total", 100*(1 - sparse_params_size/params_size), epoch)
+        self.tblogger.scalar_summary("sparsity/weights/total", 100*(1 - sparse_params_size/params_size), epoch)
        self.tblogger.sync_to_file()

    def log_weights_filter_magnitude(self, model, epoch, multi_graphs=False):

--- a/jupyter/compare_executions.ipynb
+++ b/jupyter/compare_executions.ipynb
@@ -53,7 +53,7 @@
    "\n",
    "# Choose which performance indicators you wish to graph\n",
    "tags = ['Peformance/Validation/Top1', 'Peformance/Validation/Loss', \n",
-    "        'sprasity/weights/total',     'Peformance/Training/Reg Loss']\n",
+    "        'sparsity/weights/total',     'Peformance/Training/Reg Loss']\n",
    "\n",
    "f, axs = plt.subplots(2, 2, figsize=(20,20))\n",
    "f.suptitle('Performance')\n",

 %% Cell type:markdown id: tags:

 ## Compare experiment executions

 This notebook let's you qickly compare the training progress of your experiments.
 You will need to have the tfevents files (these are TensorBoard formatted log files that Distiller creates).

 %% Cell type:code id: tags:

 ``` python
 import tensorflow as tf
 import numpy as np
 import matplotlib.pyplot as plt

 def get_performance_data(path_to_events_file, tag):
    """Extract the performance history of data named 'tag'

    Based on sample code from TF:
    https://github.com/tensorflow/tensorflow/blob/master/tensorflow/python/summary/summary_iterator.py
    """
    data = []
    steps = []
    for e in tf.train.summary_iterator(path_to_events_file):
        for v in e.summary.value:
            if v.tag == tag:
                data.append(v.simple_value)
                steps.append(e.step)
    return steps, data
 ```

 %% Cell type:code id: tags:

 ``` python
 # Here insert your own tfevents files to compare
 # WARNING: these files do not exist in the repositroy (too large) and will give you an error
 experiment_files = [('events.out.tfevents.1523290172.one-machine', 'experiment 1'),
                    ('events.out.tfevents.1520430112.one-machine', 'experiment 2')]

 # Choose which performance indicators you wish to graph
 tags = ['Peformance/Validation/Top1', 'Peformance/Validation/Loss',
-        'sprasity/weights/total',     'Peformance/Training/Reg Loss']
+        'sparsity/weights/total',     'Peformance/Training/Reg Loss']

 f, axs = plt.subplots(2, 2, figsize=(20,20))
 f.suptitle('Performance')

 for experiment in experiment_files:
    add_experiment(axs, tags, experiment[0], label=experiment[1])
 plt.tight_layout()

 plt.show()
 ```