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Testing finetuning for more Prithvi-2 backbones #322

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Dec 12, 2024
Merged

Testing finetuning for more Prithvi-2 backbones #322

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254b54f
Testing finetuning for more Prithvi-2 backbones
Joao-L-S-Almeida Dec 11, 2024
26b2031
Complete tests
Joao-L-S-Almeida Dec 11, 2024
710b7de
Testing more backbones for instantiation
Joao-L-S-Almeida Dec 11, 2024
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150 changes: 150 additions & 0 deletions tests/resources/configs/manufactured-finetune_prithvi_eo_v2_300.yaml
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Original file line number Diff line number Diff line change
@@ -0,0 +1,150 @@
# lightning.pytorch==2.1.1
seed_everything: 42
trainer:
accelerator: cpu
strategy: auto
devices: auto
num_nodes: 1
# precision: 16-mixed
logger:
class_path: TensorBoardLogger
init_args:
save_dir: tests/
name: all_ecos_random
callbacks:
- class_path: RichProgressBar
- class_path: LearningRateMonitor
init_args:
logging_interval: epoch
- class_path: EarlyStopping
init_args:
monitor: val/loss
patience: 100
max_epochs: 2
check_val_every_n_epoch: 1
log_every_n_steps: 20
enable_checkpointing: true
default_root_dir: tests/
data:
class_path: GenericNonGeoPixelwiseRegressionDataModule
init_args:
batch_size: 2
num_workers: 4
train_transform:
#- class_path: albumentations.HorizontalFlip
# init_args:
# p: 0.5
#- class_path: albumentations.Rotate
# init_args:
# limit: 30
# border_mode: 0 # cv2.BORDER_CONSTANT
# value: 0
# # mask_value: 1
# p: 0.5
- class_path: ToTensorV2
dataset_bands:
- 0
- BLUE
- GREEN
- RED
- NIR_NARROW
- SWIR_1
- SWIR_2
- 1
- 2
- 3
- 4
output_bands:
- BLUE
- GREEN
- RED
- NIR_NARROW
- SWIR_1
- SWIR_2
rgb_indices:
- 2
- 1
- 0
train_data_root: tests/resources/inputs
train_label_data_root: tests/resources/inputs
val_data_root: tests/resources/inputs
val_label_data_root: tests/resources/inputs
test_data_root: tests/resources/inputs
test_label_data_root: tests/resources/inputs
img_grep: "regression*input*.tif"
label_grep: "regression*label*.tif"
means:
- 547.36707
- 898.5121
- 1020.9082
- 2665.5352
- 2340.584
- 1610.1407
stds:
- 411.4701
- 558.54065
- 815.94025
- 812.4403
- 1113.7145
- 1067.641
no_label_replace: -1
no_data_replace: 0

model:
class_path: terratorch.tasks.PixelwiseRegressionTask
init_args:
model_args:
decoder: UperNetDecoder
pretrained: false
backbone: prithvi_eo_v2_300
# backbone_pretrained_cfg_overlay:
# file: tests/prithvi_vit_300.pt
backbone_drop_path_rate: 0.3
# backbone_window_size: 8
decoder_channels: 64
num_frames: 1
in_channels: 6
bands:
- BLUE
- GREEN
- RED
- NIR_NARROW
- SWIR_1
- SWIR_2
head_dropout: 0.5708022831486758
head_final_act: torch.nn.ReLU
head_learned_upscale_layers: 2
loss: rmse
#aux_heads:
# - name: aux_head
# decoder: IdentityDecoder
# decoder_args:
# decoder_out_index: 2
# head_dropout: 0,5
# head_channel_list:
# - 64
# head_final_act: torch.nn.ReLU
#aux_loss:
# aux_head: 0.4
ignore_index: -1
freeze_backbone: true
freeze_decoder: false
model_factory: PrithviModelFactory

# uncomment this block for tiled inference
# tiled_inference_parameters:
# h_crop: 224
# h_stride: 192
# w_crop: 224
# w_stride: 192
# average_patches: true
optimizer:
class_path: torch.optim.AdamW
init_args:
lr: 0.00013524680528283027
weight_decay: 0.047782217873995426
lr_scheduler:
class_path: ReduceLROnPlateau
init_args:
monitor: val/loss

150 changes: 150 additions & 0 deletions tests/resources/configs/manufactured-finetune_prithvi_eo_v2_600.yaml
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -0,0 +1,150 @@
# lightning.pytorch==2.1.1
seed_everything: 42
trainer:
accelerator: cpu
strategy: auto
devices: auto
num_nodes: 1
# precision: 16-mixed
logger:
class_path: TensorBoardLogger
init_args:
save_dir: tests/
name: all_ecos_random
callbacks:
- class_path: RichProgressBar
- class_path: LearningRateMonitor
init_args:
logging_interval: epoch
- class_path: EarlyStopping
init_args:
monitor: val/loss
patience: 100
max_epochs: 2
check_val_every_n_epoch: 1
log_every_n_steps: 20
enable_checkpointing: true
default_root_dir: tests/
data:
class_path: GenericNonGeoPixelwiseRegressionDataModule
init_args:
batch_size: 2
num_workers: 4
train_transform:
#- class_path: albumentations.HorizontalFlip
# init_args:
# p: 0.5
#- class_path: albumentations.Rotate
# init_args:
# limit: 30
# border_mode: 0 # cv2.BORDER_CONSTANT
# value: 0
# # mask_value: 1
# p: 0.5
- class_path: ToTensorV2
dataset_bands:
- 0
- BLUE
- GREEN
- RED
- NIR_NARROW
- SWIR_1
- SWIR_2
- 1
- 2
- 3
- 4
output_bands:
- BLUE
- GREEN
- RED
- NIR_NARROW
- SWIR_1
- SWIR_2
rgb_indices:
- 2
- 1
- 0
train_data_root: tests/resources/inputs
train_label_data_root: tests/resources/inputs
val_data_root: tests/resources/inputs
val_label_data_root: tests/resources/inputs
test_data_root: tests/resources/inputs
test_label_data_root: tests/resources/inputs
img_grep: "regression*input*.tif"
label_grep: "regression*label*.tif"
means:
- 547.36707
- 898.5121
- 1020.9082
- 2665.5352
- 2340.584
- 1610.1407
stds:
- 411.4701
- 558.54065
- 815.94025
- 812.4403
- 1113.7145
- 1067.641
no_label_replace: -1
no_data_replace: 0

model:
class_path: terratorch.tasks.PixelwiseRegressionTask
init_args:
model_args:
decoder: UperNetDecoder
pretrained: false
backbone: prithvi_eo_v2_600
# backbone_pretrained_cfg_overlay:
# file: tests/prithvi_vit_300.pt
backbone_drop_path_rate: 0.3
# backbone_window_size: 8
decoder_channels: 64
num_frames: 1
in_channels: 6
bands:
- BLUE
- GREEN
- RED
- NIR_NARROW
- SWIR_1
- SWIR_2
head_dropout: 0.5708022831486758
head_final_act: torch.nn.ReLU
head_learned_upscale_layers: 2
loss: rmse
#aux_heads:
# - name: aux_head
# decoder: IdentityDecoder
# decoder_args:
# decoder_out_index: 2
# head_dropout: 0,5
# head_channel_list:
# - 64
# head_final_act: torch.nn.ReLU
#aux_loss:
# aux_head: 0.4
ignore_index: -1
freeze_backbone: true
freeze_decoder: false
model_factory: PrithviModelFactory

# uncomment this block for tiled inference
# tiled_inference_parameters:
# h_crop: 224
# h_stride: 192
# w_crop: 224
# w_stride: 192
# average_patches: true
optimizer:
class_path: torch.optim.AdamW
init_args:
lr: 0.00013524680528283027
weight_decay: 0.047782217873995426
lr_scheduler:
class_path: ReduceLROnPlateau
init_args:
monitor: val/loss

2 changes: 1 addition & 1 deletion tests/resources/configs/manufactured-finetune_prithvi_vit_300.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -96,7 +96,7 @@ model:
model_args:
decoder: UperNetDecoder
pretrained: false
backbone: prithvi_vit_300
backbone: prithvi_eo_v2_300
# backbone_pretrained_cfg_overlay:
# file: tests/prithvi_vit_300.pt
backbone_drop_path_rate: 0.3
Expand Down
9 changes: 6 additions & 3 deletions tests/test_backbones.py
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Original file line number Diff line number Diff line change
Expand Up @@ -35,22 +35,23 @@ def input_386():
return torch.ones((1, NUM_CHANNELS, 386, 386))


@pytest.mark.parametrize("model_name", ["prithvi_eo_v1_100", "prithvi_eo_v2_300", "prithvi_swin_B"])
@pytest.mark.parametrize("model_name", ["prithvi_swin_B", "prithvi_swin_L", "prithvi_eo_v1_100", "prithvi_eo_v2_300", "prithvi_swin_B"])
@pytest.mark.parametrize("test_input", ["input_224", "input_512"])
def test_can_create_backbones_from_timm(model_name, test_input, request):
backbone = timm.create_model(model_name, pretrained=False)
input_tensor = request.getfixturevalue(test_input)
backbone(input_tensor)
gc.collect()

@pytest.mark.parametrize("model_name", ["prithvi_eo_v1_100", "prithvi_eo_v2_300", "prithvi_swin_B"])
@pytest.mark.parametrize("model_name", ["prithvi_swin_B", "prithvi_swin_L", "prithvi_eo_v1_100", "prithvi_eo_v2_300", "prithvi_swin_B"])
@pytest.mark.parametrize("test_input", ["input_224", "input_512"])
def test_can_create_backbones_from_timm_features_only(model_name, test_input, request):
backbone = timm.create_model(model_name, pretrained=False, features_only=True)
input_tensor = request.getfixturevalue(test_input)
backbone(input_tensor)
gc.collect()
@pytest.mark.parametrize("model_name", ["prithvi_eo_v1_100", "prithvi_eo_v2_300", "prithvi_swin_B"])

@pytest.mark.parametrize("model_name", ["prithvi_swin_L", "prithvi_swin_L", "prithvi_eo_v1_100", "prithvi_eo_v2_300", "prithvi_swin_B"])
@pytest.mark.parametrize("prefix", ["", "timm_"])
def test_can_create_timm_backbones_from_registry(model_name, input_224, prefix):
backbone = BACKBONE_REGISTRY.build(prefix+model_name, pretrained=False)
Expand All @@ -62,12 +63,14 @@ def test_vit_models_accept_multitemporal(model_name, input_224_multitemporal):
backbone = timm.create_model(model_name, pretrained=False, num_frames=NUM_FRAMES)
backbone(input_224_multitemporal)
gc.collect()

@pytest.mark.parametrize("model_name", ["prithvi_eo_v1_100", "prithvi_eo_v2_300"])
def test_vit_models_non_divisible_input(model_name, input_non_divisible):
#padding 'none','constant', 'reflect', 'replicate' or 'circular' default is 'none'
backbone = timm.create_model(model_name, pretrained=False, features_only=True, num_frames=NUM_FRAMES, padding='constant')
backbone(input_non_divisible)
gc.collect()

@pytest.mark.parametrize("model_name", ["prithvi_eo_v1_100", "prithvi_eo_v2_300"])
@pytest.mark.parametrize("patch_size", [8, 16])
@pytest.mark.parametrize("patch_size_time", [1, 2, 4])
Expand Down
2 changes: 1 addition & 1 deletion tests/test_finetune.py
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Original file line number Diff line number Diff line change
Expand Up @@ -22,7 +22,7 @@ def setup_and_cleanup(model_name):
if os.path.isdir(os.path.join("tests", "all_ecos_random")):
shutil.rmtree(os.path.join("tests", "all_ecos_random"))

@pytest.mark.parametrize("model_name", ["prithvi_swin_B", "prithvi_vit_100"])
@pytest.mark.parametrize("model_name", ["prithvi_swin_B", "prithvi_swin_L", "prithvi_vit_100", "prithvi_eo_v2_300", "prithvi_eo_v2_600"])
@pytest.mark.parametrize("case", ["fit", "test", "validate"])
def test_finetune_multiple_backbones(model_name, case):
command_list = [case, "-c", f"tests/resources/configs/manufactured-finetune_{model_name}.yaml"]
Expand Down
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