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Format Python code with psf/black push (#325)
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There appear to be some python formatting errors in
f1426ef. This pull request
uses the [psf/black](https://github.com/psf/black) formatter to fix
these issues.
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rhoadesScholar authored Nov 8, 2024
2 parents 67fd54e + 59f00c6 commit c5d9aea
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Showing 2 changed files with 6 additions and 3 deletions.
5 changes: 3 additions & 2 deletions dacapo/experiments/architectures/cnnectome_unet.py
Original file line number Diff line number Diff line change
Expand Up @@ -8,6 +8,7 @@

logger = logging.getLogger(__name__)


class CNNectomeUNet(Architecture):
"""
A U-Net architecture for 3D or 4D data. The U-Net expects 3D or 4D tensors
Expand Down Expand Up @@ -181,7 +182,7 @@ def __init__(self, architecture_config):
@property
def skip_gate(self):
return self._skip_gate

@skip_gate.setter
def skip_gate(self, skip):
self._skip_gate = skip
Expand Down Expand Up @@ -1081,7 +1082,7 @@ def __init__(
crop_factor=None,
next_conv_kernel_sizes=None,
activation=None,
skip_gate = True,
skip_gate=True,
):
"""
Upsample module. This module performs upsampling of the input tensor
Expand Down
4 changes: 3 additions & 1 deletion dacapo/experiments/architectures/cnnectome_unet_config.py
Original file line number Diff line number Diff line change
Expand Up @@ -133,5 +133,7 @@ class CNNectomeUNetConfig(ArchitectureConfig):
)
skip_gate: bool = attr.ib(
default=True,
metadata={"help_text": "Whether to use skip gates. using skip gates concatenates the left feature map with the right feature map which helps for training. disabling the skip gate will make the model like a encoder-decoder model. example pipeline: start with skip gate false, we can train with only raw data. then we can train with skip gate true to fine tune the model with groundtruth."},
metadata={
"help_text": "Whether to use skip gates. using skip gates concatenates the left feature map with the right feature map which helps for training. disabling the skip gate will make the model like a encoder-decoder model. example pipeline: start with skip gate false, we can train with only raw data. then we can train with skip gate true to fine tune the model with groundtruth."
},
)

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