Upload ProDiff/conf/config.py with huggingface_hub

ProDiff/conf/config.py

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+"""
+Configuration settings for the trajectory interpolation project.
+
+This file defines a function `load_config()` which returns a dictionary 
+containing various parameters grouped by their purpose (e.g., data, model, 
+diffusion, training, sampling).
+"""
+from types import SimpleNamespace
+import torch
+
+def load_config():
+    config_args = {
+        'data': {
+            'traj_length': 256, # 修正：增加长度以容纳两个1小时(120点)的遮蔽和上下文
+            'dataset': 'TKY_temporal',
+            'traj_path1': './data/',
+            'num_workers': 16,  # 增加数据加载线程，减少GPU等待
+        },
+        'train': {
+            'batch_size': 512,  # 显著降低batch_size以适应增长的traj_length，避免显存溢出
+            'n_epochs': 50,
+            'n_iters': 5000000,
+            'snapshot_freq': 5000,
+            'validation_freq': 5,
+            'dis_gpu': False,
+        },
+        'trans': {
+            'input_dim': 3,
+            'embed_dim': 512,
+            'num_layers': 4,
+            'num_heads': 8,
+            'forward_dim': 256,
+            'dropout': 0.1,
+            'N_CLUSTER': 20,
+        },
+                       'test': {
+                   'batch_size': 256,  # 同样降低测试batch size以适应增长的traj_length
+                   'last_only': True,
+               },
+        'diffusion': {
+            'beta_schedule': 'linear',
+            'beta_start': 0.0001,
+            'beta_end': 0.05,
+            'num_diffusion_timesteps': 500,
+        },
+        'model': {
+            'type': "simple",
+            'attr_dim': 8,
+            'guidance_scale': 2,
+            'in_channels': 3,
+            'out_ch': 3,
+            'ch': 128,
+            'ch_mult': [1, 2, 2, 2],
+            'num_res_blocks': 2,
+            'attn_resolutions': [16],
+            'dropout': 0.1,
+            'var_type': 'fixedlarge',
+            'resamp_with_conv': True,
+        },
+        'data_source': 'TKY',
+        'data_dir': './data/TKY/manually_split/',
+        'normalization_params_file': './data/TKY/normalization_params.json',
+    }
+    
+    # Create nested config structure to maintain compatibility
+    config = SimpleNamespace()
+    config.training = SimpleNamespace(**config_args['train'])
+    config.test = SimpleNamespace(**config_args['test'])
+    config.diffusion = SimpleNamespace(**config_args['diffusion'])
+    config.model = SimpleNamespace(**config_args['model'])
+    config.sampling = SimpleNamespace(**config_args['test'])  # Use test config for sampling
+    # Add DDIM sampling configuration for faster testing
+    config.sampling.type = 'ddim'  # Use DDIM instead of DDPM for 10x faster testing
+    config.sampling.ddim_steps = 50  # 50 steps instead of 500, 10x speedup
+    config.sampling.ddim_eta = 0.0  # Deterministic sampling
+    config.data = SimpleNamespace(**config_args['data'])
+    config.trans = SimpleNamespace(**config_args['trans'])
+    
+    config.device = 'cuda' if torch.cuda.is_available() else 'cpu'
+    config.masking_strategy = 'multi_segment' # 新增：'multi_segment'
+    config.mask_segments = [60, 60] # 修正：基于“一分钟一点”，每段遮蔽60个点
+    config.mask_ratio = 0.2
+    config.mask_points_per_hour = 60 # 修正：基于“一分钟一点”的先验知识
+    config.z_score_normalization = False
+    config.dis_gpu = False  # Distributed GPU training
+    
+    # Add missing top-level config fields  
+    config.learning_rate = 1.5e-4  # 降低学习率，提高训练稳定性
+    config.batch_size = config_args['train']['batch_size']
+    config.n_epochs = config_args['train']['n_epochs']
+    config.validation_freq = config_args['train']['validation_freq']
+    config.warmup_epochs = 5  # 减少warmup epochs，加速训练
+    config.contrastive_margin = 1.0
+    config.kmeans_memory_size = 15  # 增加K-means缓存，提高聚类效率
+    config.contrastive_loss_weight = 0.1
+    config.ce_loss_weight = 0.1
+    config.diffusion_loss_weight = 1.0
+    config.device_id = 0
+    config.use_amp = True  # 启用混合精度训练
+    config.normalization_params_file = config_args['normalization_params_file']
+    config.data_source = config_args['data_source']
+    config.data_dir = config_args['data_dir']
+    config.traj_length = config_args['data']['traj_length']
+    
+    return config