nilsleh

import matplotlib.pyplot as plt
import numpy as np
import planetary_computer as pc
import stackstac
from pystac_client import Client

import shapely.geometry
import fiona.transform

polygon = {

nilsleh

import json
import os

import matplotlib.pyplot as plt
import numpy as np
import planetary_computer as pc
import rasterio
import stackstac
from pystac_client import Client
from shapely.geometry import mapping, shape

nilsleh

import numpy as np
import torch
import torch.nn as nn
from functorch import vmap, jacrev, make_functional_with_buffers

batch_size = 2
in_channels = 5
out_channels = 20
feature_shape = 8
feature = torch.rand(batch_size, in_channels, feature_shape, feature_shape)

nilsleh

import numpy as np
import pandas as pd
from tqdm import tqdm_notebook as tqdm

import matplotlib.pyplot as plt

from darts import TimeSeries, concatenate
from darts.dataprocessing.transformers import Scaler
from darts.models import TFTModel
from darts.metrics import mape

nilsleh

import numpy as np
import pandas as pd

from darts import TimeSeries
from darts.dataprocessing.transformers import Scaler
from darts.models import TFTModel
from darts.datasets import AirPassengersDataset
from darts.utils.timeseries_generation import datetime_attribute_timeseries
from darts.utils.likelihood_models import QuantileRegression
import pytorch_lightning as pl

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import torch
import timm

from torchgeo.datasets import EuroSAT

import numpy as np
from sklearn.linear_model import LogisticRegression
from torch.utils.data import DataLoader
import torch
from tqdm import tqdm

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nilsleh

import requests

# Set up authentication with your PAT
headers = {
    'Authorization': 'Bearer YOUR_ACCESS_TOKEN'
}

# Define the repository information
repo_owner = 'repo_owner'
repo_name = 'repo_name'

nilsleh

import os
from typing import Sequence

import matplotlib.pyplot as plt
import numpy as np
import torch
import torch.backends.cudnn as cudnn
from lightning import Trainer
from lightning.pytorch import seed_everything
from orig_conformal import ConformalModel

nilsleh

"""Ocean Bench Datamodules."""

import itertools
import os
from collections import namedtuple
from typing import Any

import hydra
import numpy as np
import ocn_tools._src.geoprocessing.gridding as obgrid