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pvnet_uk_region_day_ahead

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pvnet_uk_region_day_ahead
File size: 2,219 Bytes 
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{
    "_target_": "pvnet.models.multimodal.multimodal.Model",
    "output_quantiles": [
        0.02,
        0.1,
        0.25,
        0.5,
        0.75,
        0.9,
        0.98
    ],
    "nwp_encoders_dict": {
        "ukv": {
            "_target_": "pvnet.models.multimodal.encoders.encoders3d.DefaultPVNet",
            "_partial_": true,
            "in_channels": 12,
            "out_features": 256,
            "number_of_conv3d_layers": 6,
            "conv3d_channels": 32,
            "image_size_pixels": 24
        },
        "ecmwf": {
            "_target_": "pvnet.models.multimodal.encoders.encoders3d.DefaultPVNet",
            "_partial_": true,
            "in_channels": 12,
            "out_features": 256,
            "number_of_conv3d_layers": 4,
            "conv3d_channels": 32,
            "image_size_pixels": 12
        }
    },
    "sat_encoder": {
        "_target_": "pvnet.models.multimodal.encoders.encoders3d.ResConv3DNet2",
        "_partial_": true,
        "in_channels": 11,
        "out_features": 256,
        "image_size_pixels": 24,
        "hidden_channels": 32,
        "n_res_blocks": 3,
        "res_block_layers": 3,
        "batch_norm": true,
        "dropout_frac": 0.0
    },
    "pv_encoder": null,
    "output_network": {
        "_target_": "pvnet.models.multimodal.linear_networks.networks.ResFCNet2",
        "_partial_": true,
        "fc_hidden_features": 128,
        "n_res_blocks": 6,
        "res_block_layers": 2,
        "dropout_frac": 0.0
    },
    "embedding_dim": 16,
    "include_sun": true,
    "include_gsp_yield_history": false,
    "forecast_minutes": 2160,
    "history_minutes": 120,
    "min_sat_delay_minutes": 60,
    "sat_history_minutes": 90,
    "pv_history_minutes": 120,
    "pv_interval_minutes": 30,
    "nwp_history_minutes": {
        "ukv": 120,
        "ecmwf": 120
    },
    "nwp_forecast_minutes": {
        "ukv": 1800,
        "ecmwf": 2220
    },
    "optimizer": {
        "_target_": "pvnet.optimizers.EmbAdamWReduceLROnPlateau",
        "lr": 0.0001,
        "weight_decay": 0.25,
        "amsgrad": true,
        "patience": 5,
        "factor": 0.1,
        "threshold": 0.002
    },
    "adapt_batches": true
}