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add 1em to non-12em configs
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and add a low data config
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henryaddison committed Mar 18, 2024
1 parent 164bd77 commit fc4ed24
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2 changes: 1 addition & 1 deletion bin/local-test-train
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set -euo pipefail

config_name="ukcp_local_pr_cunet_continuous"
config_name="ukcp_local_pr_1em_cunet_continuous"
dataset="bham_gcmx-4x_1em_psl-sphum4th-temp4th-vort4th_eqvt_random-season-historic"

sde="subvpsde"
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import ml_collections
import torch

from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_configs import get_default_configs as get_base_configs
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_1em_configs import get_default_configs as get_base_configs


def get_default_configs():
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# Lint as: python3
"""Training NCSN++ on precip data with sub-VP SDE."""
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_configs import get_default_configs
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_1em_configs import get_default_configs


def get_config():
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# coding=utf-8
# Copyright 2020 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

# Lint as: python3
"""Training NCSN++ on precip data with sub-VP SDE."""
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_1em_configs import get_default_configs


def get_config():
config = get_default_configs()
# training
training = config.training
training.sde = 'subvpsde'
training.continuous = True
training.reduce_mean = True
training.n_epochs = 300

# sampling
sampling = config.sampling
sampling.method = 'pc'
sampling.predictor = 'euler_maruyama'
sampling.corrector = 'none'

# data
data = config.data
data.centered = True
data.dataset_name = 'bham_gcmx-4x_1em_psl-sphum4th-temp4th-vort4th_eqvt_random-season-historic'

# model
model = config.model
model.name = 'cncsnpp'
model.scale_by_sigma = False
model.ema_rate = 0.9999
model.normalization = 'GroupNorm'
model.nonlinearity = 'swish'
model.nf = 128
model.ch_mult = (1, 2, 2, 2)
model.num_res_blocks = 4
model.attn_resolutions = (16,)
model.resamp_with_conv = True
model.conditional = True
model.fir = True
model.fir_kernel = [1, 3, 3, 1]
model.skip_rescale = True
model.resblock_type = 'biggan'
model.progressive = 'none'
model.progressive_input = 'residual'
model.progressive_combine = 'sum'
model.attention_type = 'ddpm'
model.embedding_type = 'positional'
model.init_scale = 0.
model.fourier_scale = 16
model.conv_size = 3

# data
data = config.data
data.input_transform_key = "stan"
data.target_transform_key = "sqrturrecen"

return config
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# Lint as: python3
"""Training conditional U-Net on precip data with sub-VP SDE."""
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_configs import get_default_configs
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_1em_configs import get_default_configs


def get_config():
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# Lint as: python3
"""Training NCSN++ on precip data with VE SDE."""
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_configs import get_default_configs
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_1em_configs import get_default_configs


def get_config():
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# Lint as: python3
"""Training UNet on XArray with VE SDE."""
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_configs import get_default_configs
from ml_downscaling_emulator.score_sde_pytorch_hja22.configs.default_ukcp_local_pr_1em_configs import get_default_configs


def get_config():
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