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# Copyright (C) 2021. Huawei Technologies Co., Ltd. All rights reserved.
# This program is free software; you can redistribute it and/or modify
# it under the terms of the MIT License.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# MIT License for more details.
import os
import glob
import numpy as np
import matplotlib.pyplot as plt
import torch
def intersperse(lst, item):
# Adds blank symbol
result = [item] * (len(lst) * 2 + 1)
result[1::2] = lst
return result
def parse_filelist(filelist_path, split_char="|"):
with open(filelist_path, encoding='utf-8') as f:
filepaths_and_text = [line.strip().split(split_char) for line in f]
return filepaths_and_text
def latest_checkpoint_path(dir_path, regex="grad_*.pt"):
f_list = glob.glob(os.path.join(dir_path, regex))
f_list.sort(key=lambda f: int("".join(filter(str.isdigit, f))))
x = f_list[-1]
return x
def load_checkpoint(logdir, model, num=None):
if num is None:
model_path = latest_checkpoint_path(logdir, regex="grad_*.pt")
else:
model_path = os.path.join(logdir, f"grad_{num}.pt")
print(f'Loading checkpoint {model_path}...')
model_dict = torch.load(model_path, map_location=lambda loc, storage: loc)
model.load_state_dict(model_dict, strict=False)
return model
def save_figure_to_numpy(fig):
data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
return data
def plot_tensor(tensor):
plt.style.use('default')
fig, ax = plt.subplots(figsize=(12, 3))
im = ax.imshow(tensor, aspect="auto", origin="lower", interpolation='none')
plt.colorbar(im, ax=ax)
plt.tight_layout()
fig.canvas.draw()
data = save_figure_to_numpy(fig)
plt.close()
return data
def save_plot(tensor, savepath):
plt.style.use('default')
fig, ax = plt.subplots(figsize=(12, 3))
im = ax.imshow(tensor, aspect="auto", origin="lower", interpolation='none')
plt.colorbar(im, ax=ax)
plt.tight_layout()
fig.canvas.draw()
plt.savefig(savepath)
plt.close()
return
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