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9be39c5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | {
"model_name": "ConvLSTM",
"model_type": "convlstm",
"architectures": ["ConvLSTM", "ConvLSTMCell"],
"framework": "PyTorch",
"domain": "atmosphere",
"task": "precipitation-nowcasting",
"implementation": {
"entry_point": "model/convlstm.py",
"scope": "peephole ConvLSTM encoder-forecaster for fifteen-step radar echo prediction",
"train_script": "scripts/train.py",
"inference_script": "scripts/inference.py",
"evaluation_script": "scripts/result.py",
"synthetic_data_script": "scripts/fake_data.py"
},
"architecture": {
"family": "two-layer ConvLSTM encoder and two-layer unconditional forecaster",
"input_channels": 1,
"patch_size": 2,
"patched_channels": 4,
"hidden_channels": [16, 16],
"kernel_size": 3,
"peephole": true,
"output_frames": 15,
"output_head": "1x1 convolution over concatenated forecaster states"
},
"data": {
"datasets": ["Hong Kong weather radar echo dataset"],
"protocol": "convlstm_hko_synthetic_engineering_v1",
"format": "NPZ",
"train_file": "data/train.npz",
"test_file": "data/test.npz",
"input_shape": ["N", 5, 1, 100, 100],
"target_shape": ["N", 15, 1, 100, 100],
"interval_minutes": 6,
"forecast_horizon_minutes": 90,
"rainfall_threshold_mm_h": 0.5,
"zr_parameters": {"a": 118.239, "b": 1.5241},
"required_metadata": ["format_version", "data_source"]
},
"configuration_sources": ["conf/config.yaml", "model/convlstm.py", "scripts/fake_data.py", "scripts/train.py", "scripts/inference.py", "scripts/result.py"]
}
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