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edits to run on jupyterhub gpu #7

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edits to run on jupyterhub gpu #7

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91ca59a
edits to run on jupyterhub gpu
sem0029 Apr 12, 2024
d1bc5fe
Use default prefetch_factor
paololucchino Apr 22, 2024
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4 changes: 4 additions & 0 deletions PatchTST-env.yml
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Original file line number Diff line number Diff line change
Expand Up @@ -3,11 +3,15 @@ channels:
- conda-forge
- wfp-ram
- pytorch
- nvidia
dependencies:
- python =3.10
- pip >=22
- hip-analysis >=0.2.0
- pytorch==1.11.0
- torchvision==0.12.0
- torchaudio==0.11.0
- cudatoolkit=10.2
- xbatcher
- cachey
- jupyterlab
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2 changes: 1 addition & 1 deletion PatchTST_self_supervised/src/data/datamodule.py
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Expand Up @@ -15,7 +15,7 @@ def __init__(
shuffle_train = True,
shuffle_val = False,
drop_last = True,
prefetch_factor = None
prefetch_factor: int= 2

):
super().__init__()
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4 changes: 2 additions & 2 deletions SeasonTST/SeasonTST_finetune.py
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Expand Up @@ -136,8 +136,8 @@ def load_config():
"mask_ratio": 0.4, # masking ratio for the input
"lr": 1e-3,
"batch_size": 128,
"num_workers": 6,
"prefetch_factor": 3,
"num_workers": 0,
"prefetch_factor": 2,
"n_epochs_pretrain": 1, # number of pre-training epochs,
"freeze_epochs": 0,
"n_epochs_finetune": 250,
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4 changes: 2 additions & 2 deletions SeasonTST/SeasonTST_pretrain.py
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Expand Up @@ -95,8 +95,8 @@ def load_config():
"mask_value": -99, # Value to assign to masked elements of data input
"lr": 1e-3,
"batch_size": 128,
"prefetch_factor": 3,
"num_workers": 6,
"prefetch_factor": 2,
"num_workers": 0,
"n_epochs_pretrain": 1, # number of pre-training epochs
"pretrained_model_id": 2500, # id of the saved pretrained model
}
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3 changes: 2 additions & 1 deletion SeasonTST/utils.py
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Expand Up @@ -128,7 +128,8 @@ def plot_loss(train_loss, valid_loss, save_path):
def load_data():

# Load dataset. Ensure it has no nans
PREFIX = "https://data.earthobservation.vam.wfp.org/public-share/"
#PREFIX = "https://data.earthobservation.vam.wfp.org/public-share/"
PREFIX = "/s3/scratch/public-share/"
data = xr.open_zarr(PREFIX + "patchtst/Africa_data.zarr")
data = data.sel(
longitude=slice(9, 12), latitude=slice(-1, -3), time=slice("2003-01-01", None)
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