def test_run_workload():
# Setup
aixprt.add_workload("test_workload1", "test comment", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "10", "0.02", "10", "20", "10", "100", "-1", "100", "True", "0", "0", "0", "")
aixprt.add_workload("test_workload2", "", '', "", "", "", "", "", "", "", "", "", "", "", "", "help dir")
# Try running a workload with invalid iterations
assert aixprt.run_workload('five', "Small_Workload") == 1
assert aixprt.run_workload(-2, "Small_Workload") == 1
# Try running a workload that is not in the system
assert aixprt.run_workload(3, "Not_in_System") == 1
# Sucessfully run a workload
assert aixprt.run_workload(1, "test_workload1") == 0
# Sucessfully run a command based workload
assert aixprt.run_workload(1, "test_workload2") == 0
pass
def test_remove_workload():
expected_workload1 = Workload("test_workload(I_v3)", "", "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1", 4000, 0.01, 10, 10, 10, 100, -1, 100, False, 0, 0, 0, "")
expected_workload2 = Workload("Small_Workload", "", "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1", 200, 0.01, 10, 10, 10, 100, -1, 100, False, 0, 0, 0, "")
expected_workload3 = Workload("Smaller_Workload", "", "https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1", 100, 0.01, 10, 10, 10, 100, -1, 100, False, 0, 0, 0, "")
# Ensure file is setup properly
WL_data = aixprt.get_workloads()
assert len(WL_data) == 2
assert "test_workload(I_v3)" in WL_data
assert "Small_Workload" in WL_data
# Try to remove a non-existent workload
assert aixprt.remove_workload("Not_in_file") == 0
assert len(WL_data) == 2
assert "test_workload(I_v3)" in WL_data
assert "Small_Workload" in WL_data
# Remove an existing workload
actual_workload1 = aixprt.remove_workload("test_workload(I_v3)")
WL_data = aixprt.get_workloads()
assert len(WL_data) == 1
assert not "test_workload(I_v3)" in WL_data
assert compare_workloads(expected_workload1, actual_workload1)
# Remove an existing workload that is used in a suite
suite1 = aixprt.get_suite("Small_Suite")
assert len(suite1) == 2
actual_workload2 = aixprt.remove_workload("Small_Workload")
WL_data = aixprt.get_workloads()
assert len(WL_data) == 0
assert not "Small_Workload" in WL_data
assert compare_workloads(expected_workload2, actual_workload2)
suite1 = aixprt.get_suite("Small_Suite")
assert len(suite1) == 1
assert not "Small_Workload" in suite1
# Remove a workload that occurs multiple times in multiple suites
# Setup for this particular test:
aixprt.add_workload("test_workload(I_v3)", "", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "4100", "0.01", "10", "10", "10", "100", "-1", "100", "False", "0", "0", "0", "")
aixprt.add_workload("Small_Workload", "", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "200", "0.01", "10", "10", "10", "100", "-1", "100", "False", "0", "0", "0", "")
aixprt.add_workload("Smaller_Workload", "", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "100", "0.01", "10", "10", "10", "100", "-1", "100", "False", "0", "0", "0", "")
WL_data = aixprt.get_workloads()
assert len(WL_data) == 3
suite2_A = aixprt.get_suite("Small_Suite")
assert len(suite2_A) == 1
suite2_B = aixprt.get_suite("Smaller_Suite")
assert len(suite2_B) == 2
# Now remove
actual_workload3 = aixprt.remove_workload("Smaller_Workload")
WL_data = aixprt.get_workloads()
assert len(WL_data) == 2
assert not "Smaller_Workload" in WL_data
assert compare_workloads(expected_workload3, actual_workload3)
suite2_A = aixprt.get_suite("Small_Suite")
assert len(suite2_A) == 0
assert not "Smaller_Workload" in suite2_A
suite2_B = aixprt.get_suite("Smaller_Suite")
assert len(suite2_B) == 0
assert not "Smaller_Workload" in suite2_B
def test_run_suite():
# Setup
assert aixprt.add_workload("test_workload1", "test comment", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "10", "0.02", "10", "20", "10", "100", "-2", "100", "True", "0", "0", "0", "") == 0
assert aixprt.add_workload("test_workload2", "", '', "", "", "", "", "", "", "", "", "", "", "", "", "help dir") == 0
new_suite = {
"new_suite": [
{
"name": "test_workload1",
"iterations": "2"
},
{
"name": "test_workload2",
"iterations": "1"
}
]
}
assert aixprt.add_suite(new_suite) == 0
# Run a suite sucessfully
assert aixprt.run_suite("new_suite") == 0
# Try to run a suite that does not exist
assert aixprt.run_suite("Not_in_system") == 1
pass
def add_workload(self):
"""
Actual method call to add a workload. Passes in values from the TextInput boxes.
"""
valid = aixprt.add_workload(
self.ids.name.text, self.ids.comment.text,
self.ids.tfhub_model.text, self.ids.training_steps.text,
self.ids.learning_rate.text, self.ids.testing_percentage.text,
self.ids.validation_percentage.text,
self.ids.eval_step_interval.text, self.ids.train_batch_size.text,
self.ids.test_batch_size.text, self.ids.validation_batch_size.text,
self.ids.flip_left_right.text, self.ids.random_crop.text,
self.ids.random_scale.text, self.ids.random_brightness.text,
self.ids.command.text)
# Check if the workload was added successfully
if valid != 0:
if valid == 1:
App.get_running_app().message_text = 'Workload Already Exists'
else:
App.get_running_app(
).message_text = 'Failed To Add Workload\nSee console for details.'
else:
App.get_running_app().message_text = 'Workload Added'
def test_add_workload():
WL_data = aixprt.get_workloads()
workload1 = Workload("test_workload1", "test comment", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', 4100, 0.02, 10, 20, 10, 100, -2, 100, True, 0, 0, 0, "")
# Test to ensure that the workload to be added does not exist in the file
assert not "test_workload1" in WL_data
# Then add and assert that it does exist in it
aixprt.add_workload("test_workload1", "test comment", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "4100", "0.02", "10", "20", "10", "100", "-2", "100", "True", "0", "0", "0", "")
WL_data = aixprt.get_workloads()
assert "test_workload1" in WL_data
assert compare_workloads(WL_data["test_workload1"], workload1)
# Try to add the same workload again and ensure it does not
assert len(WL_data) == 3
assert aixprt.add_workload("test_workload1", "test comment", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "4100", "0.02", "10", "20", "10", "100", "-2", "100", "True", "0", "0", "0", "") == 1
WL_data = aixprt.get_workloads()
assert len(WL_data) == 3
# Try to add invalid workloads and ensure it does not
# Workload with 1 thing wrong
invalid_1 = aixprt.add_workload("wrong_workload", "test comment", 'https://tfhub.dev/google/imagenet/inception_v3/feature_vector/1', "4100", "0.02", "1.0", "20", "10", "100", "-2", "100", "True", "0", "0", "0", "")
expected_invalid_1 = ["testing_percentage"]
WL_data = aixprt.get_workloads()
assert len(WL_data) == 3
assert len(invalid_1) == 1
assert invalid_1 == expected_invalid_1
# Workload with everything wrong (except for the comment and command parameters, which can both be empty strings)
invalid_2 = aixprt.add_workload("", "", '', "cat", "0..02", "1.0", "False", "1.0", "asdga100", "--2", "1%00", "FTrue", "z", "e", "ro", "")
expected_invalid_2 = ["name", "tfhub_model", "training_steps", "learning_rate", "testing_percentage", "validation_percentage", "eval_step_interval", "train_batch_size", "test_batch_size", "validation_batch_size", "flip_left_right", "random_crop", "random_scale", "random_brightness"]
WL_data = aixprt.get_workloads()
assert len(WL_data) == 3
assert len(invalid_2) == 14 #TODO fix after regex is corrected
assert invalid_2 == expected_invalid_2
# Add a workload with a command
WL_data = aixprt.get_workloads()
assert len(WL_data) == 3
assert aixprt.add_workload("test_workload2", "", '', "", "", "", "", "", "", "", "", "", "", "", "", "help dir") == 0
WL_data = aixprt.get_workloads()
assert len(WL_data) == 4