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Multi time step prediction #95
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Load model parameters and configurationwith open('/data4/home/rohitsuresh/graphcast_/model/params/params-GraphCast_operational-ERA5-HRES_1979-2021-resolution_0.25-pressure_levels_13-mesh_2to6-precipitation_output_only.npz', 'rb') as model: Load statisticswith open('/data4/home/rohitsuresh/graphcast_/model/stats/stats-diffs_stddev_by_level.nc', 'rb') as f: def construct_graphcast(model_config: graphcast.ModelConfig, task_config: graphcast.TaskConfig): @hk.transform_with_state def with_configs(fn): def with_params(fn): def drop_state(fn): run_forward_jitted = drop_state(with_params(jax.jit(with_configs(run_forward.apply)))) class Predictor: Assuming inputs, targets, and forcings are already preparedpredictions = Predictor.predict(inputs, targets, forcings) ValueError: 'grid2mesh_gnn/ |
Im struggling to implement a multi time step model where i use my prediction outputs as an input for the next iteration. Can someone please help me on this.
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