Merge pull request #20 from janelia-cellmap/zouinkhim_fixes

bug fixes and better logs

dacapo/experiments/datasplits/datasets/arrays/concat_array.py

@@ -5,6 +5,9 @@
 import numpy as np
 
 from typing import Dict, Any
+import logging
+
+logger = logging.getLogger(__file__)
 
 
 class ConcatArray(Array):
@@ -116,5 +119,7 @@ def __getitem__(self, roi: Roi) -> np.ndarray:
             axis=0,
         )
         if concatenated.shape[0] == 1:
-            raise Exception(f"{concatenated.shape}, shapes")
+            logger.info(
+                f"Concatenated array has only one channel: {self.name} {concatenated.shape}"
+            )
         return concatenated

dacapo/experiments/datasplits/datasets/arrays/dvid_array.py

@@ -41,7 +41,7 @@ def attrs(self):
 
     @property
     def axes(self):
-        return ["t", "z", "y", "x"][-self.dims :]
+        return ["c", "z", "y", "x"][-self.dims :]
 
     @property
     def dims(self) -> int:

dacapo/experiments/datasplits/datasets/arrays/numpy_array.py

@@ -35,7 +35,7 @@ def from_gp_array(cls, array: gp.Array):
             ((["b", "c"] if len(array.data.shape) == instance.dims + 2 else []))
             + (["c"] if len(array.data.shape) == instance.dims + 1 else [])
             + [
-                "t",
+                "c",
                 "z",
                 "y",
                 "x",

dacapo/experiments/datasplits/datasets/arrays/zarr_array.py

@@ -54,7 +54,7 @@ def axes(self):
                 f"Zarr {self.file_name} and dataset {self.dataset} has attributes: {list(self._attributes.items())}\n"
                 f"Using default {['t', 'z', 'y', 'x'][-self.dims::]}",
             )
-            return ["t", "z", "y", "x"][-self.dims : :]
+            return ["c", "z", "y", "x"][-self.dims : :]
 
     @property
     def dims(self) -> int:

dacapo/experiments/model.py

@@ -24,7 +24,7 @@ def __init__(
         self,
         architecture: Architecture,
         prediction_head: torch.nn.Module,
-        eval_activation: torch.nn.Module = None,
+        eval_activation: torch.nn.Module | None = None,
     ):
         super().__init__()
 

dacapo/train.py

@@ -16,6 +16,7 @@ def train(run_name: str, compute_context: ComputeContext = LocalTorch()):
     """Train a run"""
 
     if compute_context.train(run_name):
+        logger.error("Run %s is already being trained", run_name)
         # if compute context runs train in some other process
         # we are done here.
         return
@@ -96,7 +97,8 @@ def train_run(
             weights_store.retrieve_weights(run, iteration=trained_until)
 
         elif latest_weights_iteration > trained_until:
-            raise RuntimeError(
+            weights_store.retrieve_weights(run, iteration=latest_weights_iteration)
+            logger.error(
                 f"Found weights for iteration {latest_weights_iteration}, but "
                 f"run {run.name} was only trained until {trained_until}."
             )

dacapo/validate.py

@@ -141,13 +141,15 @@ def validate_run(
         prediction_array_identifier = array_store.validation_prediction_array(
             run.name, iteration, validation_dataset
         )
+        logger.info("Predicting on dataset %s", validation_dataset.name)
         predict(
             run.model,
             validation_dataset.raw,
             prediction_array_identifier,
             compute_context=compute_context,
             output_roi=validation_dataset.gt.roi,
         )
+        logger.info("Predicted on dataset %s", validation_dataset.name)
 
         post_processor.set_prediction(prediction_array_identifier)
 

setup.py

@@ -36,5 +36,9 @@
         "funlib.evaluate @ git+https://github.com/pattonw/funlib.evaluate",
         "gunpowder>=1.3",
         "lsds>=0.1.3",
+        "xarray",
+        "cattrs",
+        "numpy-indexed",
+        "click",
     ],
 )