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# Copyright (c) 2024 Bytedance Ltd. and/or its affiliates | |
# | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
import torch | |
import matplotlib.pyplot as plt | |
class Chart: | |
def __init__(self): | |
self.loss_list = [] | |
def add_ckpt(self, ckpt_path, line_name): | |
ckpt = torch.load(ckpt_path, map_location="cpu") | |
train_step_list = ckpt["train_step_list"] | |
train_loss_list = ckpt["train_loss_list"] | |
val_step_list = ckpt["val_step_list"] | |
val_loss_list = ckpt["val_loss_list"] | |
val_step_list = [val_step_list[0]] + val_step_list[4::5] | |
val_loss_list = [val_loss_list[0]] + val_loss_list[4::5] | |
self.loss_list.append((line_name, train_step_list, train_loss_list, val_step_list, val_loss_list)) | |
def draw(self, save_path, plot_val=True): | |
# Global settings | |
plt.rcParams["font.size"] = 14 | |
plt.rcParams["font.family"] = "serif" | |
plt.rcParams["font.sans-serif"] = ["Arial", "DejaVu Sans", "Lucida Grande"] | |
plt.rcParams["font.serif"] = ["Times New Roman", "DejaVu Serif"] | |
# Creating the plot | |
plt.figure(figsize=(7.766, 4.8)) # Golden ratio | |
for loss in self.loss_list: | |
if plot_val: | |
(line,) = plt.plot(loss[1], loss[2], label=loss[0], linewidth=0.5, alpha=0.5) | |
line_color = line.get_color() | |
plt.plot(loss[3], loss[4], linewidth=1.5, color=line_color) | |
else: | |
plt.plot(loss[1], loss[2], label=loss[0], linewidth=1) | |
plt.xlabel("Step") | |
plt.ylabel("Loss") | |
legend = plt.legend() | |
# legend = plt.legend(loc='upper right', bbox_to_anchor=(1, 0.82)) | |
# Adjust the linewidth of legend | |
for line in legend.get_lines(): | |
line.set_linewidth(2) | |
plt.savefig(save_path, transparent=True) | |
plt.close() | |
if __name__ == "__main__": | |
chart = Chart() | |
# chart.add_ckpt("output/syncnet/train-2024_10_25-18:14:43/checkpoints/checkpoint-10000.pt", "w/ self-attn") | |
# chart.add_ckpt("output/syncnet/train-2024_10_25-18:21:59/checkpoints/checkpoint-10000.pt", "w/o self-attn") | |
chart.add_ckpt("output/syncnet/train-2024_10_24-21:03:11/checkpoints/checkpoint-10000.pt", "Dim 512") | |
chart.add_ckpt("output/syncnet/train-2024_10_25-18:21:59/checkpoints/checkpoint-10000.pt", "Dim 2048") | |
chart.add_ckpt("output/syncnet/train-2024_10_24-22:37:04/checkpoints/checkpoint-10000.pt", "Dim 4096") | |
chart.add_ckpt("output/syncnet/train-2024_10_25-02:30:17/checkpoints/checkpoint-10000.pt", "Dim 6144") | |
chart.draw("ablation.pdf", plot_val=True) | |