[2178] Add data reader for offgrid inference

config/config_offgrid_forecasting.yml

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+# (C) Copyright 2025 WeatherGenerator contributors.
+#
+# This software is licensed under the terms of the Apache Licence Version 2.0
+# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
+#
+# In applying this licence, ECMWF does not waive the privileges and immunities
+# granted to it by virtue of its status as an intergovernmental organisation
+# nor does it submit to any jurisdiction.
+
+embed_orientation: "channels"
+embed_unembed_mode: "block"
+embed_dropout_rate: 0.1
+
+ae_local_dim_embed: 2048
+ae_local_num_blocks: 0
+ae_local_num_heads: 16
+ae_local_dropout_rate: 0.1
+ae_local_with_qk_lnorm: True
+
+ae_local_num_queries: 1
+ae_local_queries_per_cell: False
+ae_adapter_num_heads: 16
+ae_adapter_embed: 128
+ae_adapter_with_qk_lnorm: True
+ae_adapter_with_residual: True
+ae_adapter_dropout_rate: 0.1
+
+ae_global_dim_embed: 2048
+ae_global_num_blocks: 4
+ae_global_num_heads: 32
+ae_global_dropout_rate: 0.1
+ae_global_with_qk_lnorm: True
+# TODO: switching to < 1 triggers triton-related issues.
+# See https://github.com/ecmwf/WeatherGenerator/issues/1050
+ae_global_att_dense_rate: 1.0
+ae_global_block_factor: 64
+ae_global_mlp_hidden_factor: 2
+ae_global_trailing_layer_norm: False
+
+ae_aggregation_num_blocks: 0
+ae_aggregation_num_heads: 32
+ae_aggregation_dropout_rate: 0.1
+ae_aggregation_with_qk_lnorm: True
+ae_aggregation_att_dense_rate: 1.0
+ae_aggregation_block_factor: 64
+ae_aggregation_mlp_hidden_factor: 2
+
+decoder_type: PerceiverIOCoordConditioning #  Main options PerceiverIOCoordConditioning or Linear
+pred_adapter_kv: False
+pred_self_attention: True
+pred_dyadic_dims: False
+pred_mlp_adaln: True
+num_class_tokens: 0
+num_register_tokens: 0
+
+# number of steps offset applied to first target window; if set to zero and forecast_steps=0 then
+# one is training an auto-encoder
+fe_num_blocks: 16
+fe_num_heads: 16
+fe_dropout_rate: 0.1
+fe_with_qk_lnorm: True
+fe_layer_norm_after_blocks: [7]  # Index starts at 0. Thus, [3] adds a LayerNorm after the fourth layer
+fe_impute_latent_noise_std: 1e-4
+# currently fixed to 1.0 (due to limitations with flex_attention and triton)
+forecast_att_dense_rate: 1.0
+
+healpix_level: 5
+
+rope_2D: False
+
+with_mixed_precision: True
+with_flash_attention: True
+compile_model: False
+with_fsdp: True
+attention_dtype: bf16
+mixed_precision_dtype: bf16
+mlp_norm_eps: 1e-5
+norm_eps: 1e-4
+
+latent_noise_kl_weight: 0.0 # 1e-5
+latent_noise_gamma: 2.0
+latent_noise_saturate_encodings: 5 
+latent_noise_use_additive_noise: False
+latent_noise_deterministic_latents: True 
+
+freeze_modules: ""
+load_chkpt: {}
+
+norm_type: "LayerNorm"
+qk_norm_type: null  # if null, defaults to norm_type
+
+#####################################
+
+streams_directory: "./config/streams/era5_1deg_forecasting/"
+streams: ???
+
+# type of zarr_store
+zarr_store: "zip" # "zarr" for LocalStore, "zip" for ZipStore
+
+general:
+
+  # mutable parameters
+  istep: 0
+  rank: ???
+  world_size: ???
+
+  # local_rank, 
+  # with_ddp,
+  # data_path_*, 
+  # model_path, 
+  # run_path, 
+  # path_shared_
+
+  multiprocessing_method: "fork"
+
+  desc: ""
+  run_id: ???
+  run_history: []
+
+# logging frequency in the training loop (in number of batches)
+train_logging:
+  terminal: 10
+  metrics: 20
+  checkpoint: 250
+
+# parameters for data loading
+data_loading :
+
+  num_workers: 12
+  rng_seed: ???
+  repeat_data_in_mini_epoch : False
+
+
+# config for training
+training_config:
+
+  # training_mode: "masking", "student_teacher", "latent_loss"
+  training_mode: ["masking"]
+
+  num_mini_epochs: 64
+  samples_per_mini_epoch: 4096
+  shuffle: True
+
+  start_date: 1979-01-01T00:00
+  end_date: 2022-12-31T00:00
+
+  time_window_step: 06:00:00
+  time_window_len: 06:00:00
+
+  learning_rate_scheduling :
+    lr_start: 1e-6
+    lr_max: 5e-5
+    lr_final_decay: 2e-6
+    lr_final: 0.0
+    num_steps_warmup: 256
+    num_steps_cooldown: 512
+    policy_warmup: "cosine"
+    policy_decay: "constant"
+    policy_cooldown: "linear"
+    parallel_scaling_policy: "sqrt"
+
+  optimizer:
+    grad_clip: 1.0
+    weight_decay: 0.1
+    log_grad_norms: False
+    adamw :
+      # parameters are scaled by number of DDP workers
+      beta1 : 0.98125 # == 0.85 on 2 nodes x 4 gpus
+      beta2 : 0.9875  # == 0.90 on 2 nodes x 4 gpus
+      eps : 2e-08
+
+  losses : {
+    "physical": {
+        type: LossPhysical,
+        loss_fcts: { "mse": { }, },
+        },
+    }
+
+  model_input: {
+    "forecasting" : {
+      # masking strategy: "random", "healpix", "forecast"
+      masking_strategy: "forecast",
+      },
+    }
+
+  forecast :
+      time_step: 06:00:00
+      offset: 1
+      num_steps: 3
+      policy: "fixed"
+
+
+# validation config; full validation config is merge of training and validation config
+validation_config: 
+
+  samples_per_mini_epoch: 256
+  shuffle: False
+
+  start_date: 2023-10-01T00:00
+  end_date: 2023-12-31T00:00
+
+  # whether to track the exponential moving average of weights for validation
+  validate_with_ema: 
+    enabled : True
+    ema_ramp_up_ratio: 0.09
+    ema_halflife_in_thousands: 1e-3
+
+  # parameters for validation samples that are written to disk
+  output : {
+    # number of samples that are written
+    num_samples: 0,
+    # write samples in normalized model space
+    normalized_samples: False,
+    # output streams to write; default all
+    streams: null,
+    }
+
+  # run validation before training starts (mainly for model development)
+  validate_before_training: False
+
+
+# test config; full test config is merge of validation and test config
+# test config is used by default when running inference
+
+test_config:
+
+  offgrid_eval:
+    # absolute path to .npy file with shape (N, 2) [lat, lon] used for offgrid inference
+    grid: /e/scratch/weatherai/shared_work/offgrid-test/offgrid_regular.npy
+    # temporal spacing between offgrid samples, e.g. 6h
+    frequency: 6h
+    # TODO add support for geoinfos
+    geoinfos: null
+
+# Tags for experiment tracking
+# These tags will be logged in MLFlow along with completed runs for train, eval, val
+# The tags are free-form, with the following rules:
+# - tags should be primitive types (strings, numbers, booleans). NO lists or dictionaries
+# - tags should not duplicate existing config entries.
+# - try to reuse existing tags where possible. MLFlow does not like having too many unique tags
+# - do not use long strings in values (less than 20 characters is a good rule of thumb, we may enforce this in the future)
+wgtags:
+  # The name of the organization of the person running the experiment.
+  # This may be autofilled in the future. Expected values are lowercase strings 
+  # e.g. "ecmwf", "cmcc", "metnor", "jsc", "escience"
+  org: null
+  # The Github issue corresponding to this run (number such as 1234)
+  # Github issues are the central point when running experiment and contain 
+  # links to hedgedocs, code branches, pull requests etc.
+  # It is recommended to associate a run with a Github issue.
+  issue: null
+  # The name of the experiment. This is a distinctive codename for the experiment campaign being run.
+  # This is expected to be the primary tag for comparing experiments in MLFlow, along with the
+  # issue number.
+  # Expected values are lowercase strings with no spaces, just underscores:
+  # Examples: "rollout_ablation_grid"  
+  exp: null
+  # *** Experiment-specific tags ***
+  # All extra tags (including lists, dictionaries, etc.) are treated 
+  # as strings by mlflow, so treat all extra tags as simple string key: value pairs.
+  grid: null

config/evaluate/eval_config_offgrid.yml

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+#optional: if commented out all is taken care of by the default settings
+# NB. global options apply to all run_ids
+global_plotting_options:
+ regions: ["global"]
+#  image_format : "png" #options: "png", "pdf", "svg", "eps", "jpg" ..
+#  animation_format: "gif" #options: "mp4", "gif"
+#  dpi_val : 300
+#  fps: 2
+#  ERA5:
+#    marker_size: 2
+#    scale_marker_size: 1
+#    marker: "o"
+#    alpha: 0.5
+#    add_healpix_grid: false
+#    healpix_nside: 4
+#    2t: 
+#      vmin: 250
+#      vmax: 300
+#    10u:
+#      vmin: -40
+#      vmax: 40
+
+# max_workers: 36  # hard cap on parallel workers (I/O, plotting, scoring)
+
+evaluation:
+  metrics: ["rmse", "mae"]
+  regions: ["global", "nhem"]
+  summary_plots : true
+  ratio_plots : false
+  heat_maps : false
+  summary_dir: "./plots/"
+  plot_ensemble: "members" #supported: false, "std", "minmax", "members"
+  plot_score_maps: false #plot scores on a 2D maps. it slows down score computation 
+  print_summary: false #print out score values on screen. it can be verbose
+  log_scale: false
+  add_grid: false
+  score_cards: false
+  bar_plots: false
+
+
+default_streams:
+  ERA5:
+    channels: ["2t", "10u", "10v", "10ff", "q_1000"]
+    evaluation:
+      forecast_step: "all"
+      sample: "all"
+      ensemble: "all" #supported: "all", "mean", [0,1,2]
+    plotting:
+      sample: [0]
+      forecast_step: "all" #supported: "all", [1,2,3,...], "1-50" (equivalent of [1,2,3,...50])
+      plot_maps: true
+      plot_histograms: false
+      plot_animations: true
+
+run_ids :
+  toqb9dv6:
+    label: "test offgrid regular"
+
+  thb1rpuj:
+    label: "test offgrid synop"