enabling errors for gpu-disabled devices

httomo/cli.py

@@ -16,7 +16,7 @@
 from httomo.runner.pipeline import Pipeline
 from httomo.sweep_runner.param_sweep_runner import ParamSweepRunner
 from httomo.transform_layer import TransformLayer
-from httomo.utils import log_exception, mpi_abort_excepthook
+from httomo.utils import log_exception, log_once, mpi_abort_excepthook
 from httomo.yaml_checker import validate_yaml_config
 from httomo.runner.task_runner import TaskRunner
 from httomo.ui_layer import UiLayer, PipelineFormat
@@ -312,21 +312,22 @@ def _set_gpu_id(gpu_id: int):
     try:
         import cupy as cp
 
-        gpu_count = cp.cuda.runtime.getDeviceCount()
+        if cp.cuda.is_available():
+            gpu_count = cp.cuda.runtime.getDeviceCount()
 
-        if gpu_id != -1:
-            if gpu_id not in range(0, gpu_count):
-                raise ValueError(
-                    f"GPU Device not available for access. Use a GPU ID in the range: 0 to {gpu_count} (exclusive)"
-                )
+            if gpu_id != -1:
+                if gpu_id not in range(0, gpu_count):
+                    raise ValueError(
+                        f"GPU Device not available for access. Use a GPU ID in the range: 0 to {gpu_count} (exclusive)"
+                    )
 
-            cp.cuda.Device(gpu_id).use()
-
-        httomo.globals.gpu_id = gpu_id
-
-    except ImportError:
-        pass  # silently pass and run if the CPU pipeline is given
+                cp.cuda.Device(gpu_id).use()
+        else:
+            log_once("CuPy is installed but the GPU device is inaccessible. Only CPU pipelines would work.")
 
+            httomo.globals.gpu_id = gpu_id
+    except ImportError as e:
+        log_exception(f"CuPy is not installed {e}. Only CPU pipelines would work.")
 
 def set_global_constants(
     out_dir: Path,

httomo/method_wrappers/generic.py

@@ -326,7 +326,7 @@ def execute(self, block: T) -> T:
             block = self._run_method(block, args)
             block = self._postprocess_data(block)
 
-        if xp.get_array_module(block.data).__name__ == "cupy":
+        if gpu_enabled:
             self._gpu_time_info.kernel = t.elapsed
         else:
             self._gpu_time_info.kernel = 0

httomo/method_wrappers/rotation.py

@@ -2,11 +2,9 @@
 from httomo.method_wrappers.generic import GenericMethodWrapper
 from httomo.runner.method_wrapper import MethodParameterDictType
 from httomo.runner.methods_repository_interface import MethodRepository
-from httomo.utils import catchtime, log_once, xp
+from httomo.utils import catchtime, log_once, xp, gpu_enabled
 
 from httomo_backends.methods_database.query import Pattern
-
-
 import numpy as np
 from mpi4py import MPI
 from mpi4py.MPI import Comm
@@ -209,7 +207,8 @@ def _run_method(self, block: T, args: Dict[str, Any]) -> T:
                     self._gpu_time_info.host2device += t.elapsed
                 if not self.cupyrun:
                     with catchtime() as t:
-                        sino_slice = xp.asnumpy(sino_slice)
+                        if gpu_enabled:
+                            sino_slice = xp.asnumpy(sino_slice)
                     self._gpu_time_info.device2host += t.elapsed
                 args["ind"] = 0
                 args[self.parameters[0]] = sino_slice[:, xp.newaxis, :]

httomo/sweep_runner/param_sweep_runner.py

@@ -20,9 +20,6 @@
 from httomo.runner.gpu_utils import get_available_gpu_memory, gpumem_cleanup
 from httomo.preview import PreviewConfig, PreviewDimConfig
 from httomo.runner.dataset_store_interfaces import DataSetSource
-from httomo_backends.methods_database.packages.backends.httomolibgpu.supporting_funcs.prep.phase import (
-    _calc_memory_bytes_for_slices_paganin_filter,
-)
 
 
 class ParamSweepRunner:
@@ -312,12 +309,17 @@ def _preview_modifier(
 def _slices_to_fit_memory_Paganin(source: DataSetSource) -> int:
     """
     Estimating the number of vertical slices that can fit on the device for running the Paganin method.
+    This function assumes that it is running on the GPU-enabled machine
 
     For the Paganin method, the filter kernel width can vary. Therefore, we aim to use the tallest possible
     vertical preview that the current device can accommodate.
     If the kernel width exceeds the height of the vertical preview, some deviations are expected between
     the sweep-run results and the results obtained from processing the full dataset.
     """
+    from httomo_backends.methods_database.packages.backends.httomolibgpu.supporting_funcs.prep.phase import (
+        _calc_memory_bytes_for_slices_paganin_filter,
+    )
+
     available_memory = get_available_gpu_memory(10.0)
     angles_total = source.aux_data.angles_length
     det_X_length = source.chunk_shape[2]