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""" Class for visualizing after compression is completed"""
import pickle
import pandas as pd
from bokeh.models import ColumnDataSource, DataTable, TableColumn
from aimet_common.compression_algo import CompressionAlgo
from aimet_common.bokeh_plots import BokehServerSession
from aimet_common import plotting_utils
[docs]class VisualizeCompression:
""" Updates bokeh server session document and publishes graphs/tables to the server with session id compression. """
def __init__(self, visualization_url):
self.bokeh_session = BokehServerSession(visualization_url, session_id="compression")
self.__document = self.bokeh_session.document
[docs] def display_eval_scores(self, saved_eval_scores_dict_path):
"""
Publishes the evaluation scores table to the server.
:param saved_eval_scores_dict_path: file path to the evaluation scores for each layer
:return: None
"""
with open(saved_eval_scores_dict_path, 'rb') as infile:
eval_scores_dict = pickle.load(infile)
eval_scores_data_frame = pd.DataFrame.from_dict(eval_scores_dict).T
eval_scores_data_frame.columns = eval_scores_data_frame.columns.map(str)
eval_scores_data_frame.insert(0, 'layers', eval_scores_data_frame.index)
source = ColumnDataSource(data=eval_scores_data_frame)
columns = [TableColumn(field=Ci, title=Ci) for Ci in eval_scores_data_frame.columns] # bokeh columns
eval_scores_data_table = DataTable(source=source, columns=columns, width=1500)
self.__document.add_root(eval_scores_data_table)
[docs] def display_comp_ratio_plot(self, comp_ratio_list_path):
"""
Publishes the optimal compression ratios to the server.
:param comp_ratio_list_path: Path to the pkl file with compression ratios for each layer
:return: None
"""
layer_comp_ratio_list = CompressionAlgo.unpickle_comp_ratios_list(comp_ratio_list_path=comp_ratio_list_path)
# visualize comp ratios vs layers in a plot and add it to a server session document.
comp_ratios = []
layer_names = []
for layer_name, comp_ratio in layer_comp_ratio_list:
comp_ratios.append(comp_ratio)
layer_names.append(layer_name)
plot = plotting_utils.plot_optimal_compression_ratios(comp_ratios, layer_names)
self.__document.add_root(plot)