<jupyter_start><jupyter_text>Import Libraries<jupyter_code>!pip install -r ../../requirements.txt
import sys
sys.path.insert(0,'../..')
import matplotlib.pyplot as plt
import matplotlib.image as pltimg
import util.util as util
import os, time
from train import train
from test import test<jupyter_output><empty_output><jupyter_text>Data Analysis and Preprocessing<jupyter_code>util.visualize_unpaired("data", kind="val")
util.resolution_distribution("data", kind="val")<jupyter_output><empty_output><jupyter_text>Evaluate Model<jupyter_code>start_time = time.time()
test(['--dataroot=./data/valA','--name=baseline','--model=test','--checkpoints_dir=./model-checkpoints','--gpu_ids=0','--no_dropout','--preprocess=none'])
print("Time: {} Seconds".format(time.time()-start_time))<jupyter_output>----------------- Options ---------------
             aspect_ratio: 1.0                           
               batch_size: 1                             
          checkpoints_dir: ./model-checkpoints           	[default: ./checkpoints]
                crop_size: 256                           
                 dataroot: ./data/valA                   	[default: None]
             dataset_mode: single                        
                direction: AtoB                          
          display_winsize: 256                           
                    epoch: latest                        
                     eval: False                         
                  gpu_ids: 0                             
                init_gain: 0.02                          
                init_type: normal                        
                 input_nc: 3                             
                  isTrain: False                         	[default: None]
                load_iter: 0   [...]
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{'chain_length': '3', 'dir': 'jupyter-structured-clean-dedup', 'id': '282381', 'license': 'BSD-3-Clause', 'n_tokens_mistral': 481, 'n_tokens_neox': 448, 'n_words': 81, 'path': 'translations/van-gogh-landscape/validation.ipynb', 'repo_name': 'moritztng/pytorch-CycleGAN-and-pix2pix', 'size': '1798'}