update for agent to work with demo

controller.py

@@ -17,7 +17,7 @@ pipe.add_parameter(
     'data/mnist_png/testing'
 )
 
-pipe.set_default_execution_queue("default")
+pipe.set_default_execution_queue("docker_image")
 # pipe.set_default_execution_queue('test')
 
  # Adding the first stage to the pipeline, a clone of the base tasks will be created and used
@@ -39,8 +39,8 @@ pipe.add_step(name='stage_train',
                 )
 
 # Starting the pipeline
-pipe.start_locally(run_pipeline_steps_locally=True)
+#pipe.start_locally(run_pipeline_steps_locally=True)
 # comment line above and uncomment line below to run scrips on queue test on which agents are listening
-#pipe.start(queue='test')
+pipe.start(queue='docker_image')
 
 print('done')

stage_one.py

 from clearml import Task, Dataset
 
-Task.add_requirements("-r ./requirements.txt")
+#Task.add_requirements("-r ./requirements.txt")
 task = Task.init(project_name="pipeline",
                 task_name="pipeline step 1 dataset artifact",
                 output_uri=True)

stage_two.py

@@ -75,7 +75,7 @@ def validate(model, testloader, criterion):
     epoch_acc = 100. * (valid_running_correct / len(testloader.dataset))
     return epoch_loss, epoch_acc
 
-Task.add_requirements("-r ./requirements.txt")
+#Task.add_requirements("-r ./requirements.txt")
 task = Task.init(project_name="pipeline",
                 task_name="pipeline step 2 train model",
                 output_uri=True)