draft for flexynesis gpu rule and condor_container_gpu model rule

Author: mira-miracoli

files/galaxy/tpv/destinations.yml.j2

@@ -555,12 +555,43 @@ destinations:
     max_accepted_mem: 500
     min_accepted_gpus: 1
     max_accepted_gpus: 4
+    env:
+      GPU_AVAILABLE: 1
+    context:
+      galaxy_group: 'GalaxyGroup == "pxe-gpu"'
     params:
-      requirements: 'GalaxyGroup == "pxe-gpu"'
+      requirements: "{galaxy_group}"
+      request_gpus: "{gpus or 0}"
       docker_run_extra_arguments: "{entity.params.get('docker_run_extra_arguments') or ''} --gpus all --env CUDA_VISIBLE_DEVICES=$_CONDOR_AssignedGPUs --env NVIDIA_VISIBLE_DEVICES=$_CONDOR_AssignedGPUs"
       singularity_run_extra_arguments: "{entity.params.get('singularity_run_extra_arguments') or ''} --nv --env CUDA_VISIBLE_DEVICES=$_CONDOR_AssignedGPUs"
-    env:
-      GPU_AVAILABLE: 1
+    rules:
+      - id: GPU model preferences
+        if: |
+          "exclude_gpu_models" in entity.context or "include_gpu_models" in entity.context
+        execute: |
+          exclude_gpu_models = entity.context.get('exclude_gpu_models', [])
+          include_gpu_models = entity.context.get('include_gpu_models', [])
+          existing_requirements = galaxy_group
+          gpu_conditions_list = []
+          if exclude_gpu_models:
+              exclude_conditions = ' && '.join(
+                  f'(GPUs_DeviceName != "{model}")' for model in exclude_gpu_models
+              )
+              gpu_conditions_list.append(exclude_conditions)
+          if include_gpu_models:
+              include_conditions = ' || '.join(
+                  f'(GPUs_DeviceName == "{model}")' for model in include_gpu_models
+              )
+              gpu_conditions_list.append(f'({include_conditions})')
+          # Combine all GPU conditions with AND
+          if gpu_conditions_list:
+              gpu_conditions = ' && '.join(gpu_conditions_list)
+              # Combine with existing requirements with AND
+              if existing_requirements:
+                  entity.params['requirements'] = f'{gpu_conditions} && ({existing_requirements})'
+              else:
+                  entity.params['requirements'] = gpu_conditions
+
 
   # This means a GPU can be shared by max 4 jobs at the same time
   condor_container_gpu_divide4:

files/galaxy/tpv/tools.yml

@@ -808,23 +808,25 @@ tools:
 
   toolshed.g2.bx.psu.edu/repos/bgruening/flexynesis/flexynesis/.*:
     rules:
-      - if: helpers.tool_version_gte(tool, '1.1.11+galaxy0')
-        gpus: 1
-        params:
-          docker_run_extra_arguments: --user 999
       - id: flexynesis_gnn_high_mem
         if: |
           retval = False
-          options = job.get_param_values(app)
-          if options:
-            training_type = options.get('training_type', {})
-            if training_type and isinstance(training_type, dict):
-              model_select = training_type.get('model_class', {})
-              if model_select and isinstance(model_select, dict):
-                retval = model_select.get('model_class') == 'GNN'
+          if helpers.tool_version_gte(tool, '1.1.11+galaxy0'):
+            options = job.get_param_values(app)
+            if options:
+              training_type = options.get('training_type', {})
+              if training_type and isinstance(training_type, dict):
+                model_select = training_type.get('model_class', {})
+                if model_select and isinstance(model_select, dict):
+                  retval = model_select.get('model_class') == 'GNN'
           retval
+        gpu: 1
         cores: 20
         mem: 100
+        params:
+          docker_run_extra_arguments: --user 999
+        context:
+          exclude_gpu_models: ["Tesla T4"] # T4 GPUs have only 16 GB of memory, which is not enough for the GNN model
 
   toolshed.g2.bx.psu.edu/repos/genouest/helixer/helixer/.*:
     params: