def test_trainer_without_optimizer(self, simple_model, loss):
""" Tests if we can compile a Executor instance without an optimizer.
"""
simple_model.parse(None)
simple_model.build()
trainer = Executor(model=simple_model, loss=loss)
trainer.compile()
def test_evaluator(self, simple_model):
""" Tests if we can compile an Executor instance.
"""
simple_model.parse(None)
simple_model.build()
evaluator = Executor(model=simple_model)
evaluator.compile()
def test_evaluator(self, simple_model): """ Tests if we can compile an Executor instance. """ simple_model.parse(None) simple_model.build() evaluator = Executor( model=simple_model ) evaluator.compile()
def test_uber_test(self, uber_model, uber_data, jinja_engine, loss):
""" Tests that we can compile and test a diverse model.
"""
uber_model.parse(jinja_engine)
uber_model.register_provider(uber_data)
uber_model.build()
trainer = Executor(model=uber_model, loss=loss)
trainer.compile()
trainer.test(providers={'default': uber_data})
def test_uber_train(self, uber_model, uber_data, jinja_engine, loss,
optimizer):
""" Tests that we can compile and train a diverse model.
"""
uber_model.parse(jinja_engine)
uber_model.register_provider(uber_data)
uber_model.build()
trainer = Executor(model=uber_model, loss=loss, optimizer=optimizer)
trainer.compile()
trainer.train(provider=uber_data, stop_when={'epochs': 1})
def test_trainer_without_optimizer(self, simple_model, loss): """ Tests if we can compile a Executor instance without an optimizer. """ simple_model.parse(None) simple_model.build() trainer = Executor( model=simple_model, loss=loss ) trainer.compile()
def test_uber_test(self, uber_model, uber_data, jinja_engine, loss):
""" Tests that we can compile and test a diverse model.
"""
uber_model.parse(jinja_engine)
uber_model.register_provider(uber_data)
uber_model.build()
trainer = Executor(
model=uber_model,
loss=loss
)
trainer.compile()
trainer.test(providers={'default' : uber_data})
def test_uber_train(self, uber_model, uber_data, jinja_engine, loss,
optimizer):
""" Tests that we can compile and train a diverse model.
"""
if uber_model.get_backend().get_name() == 'keras' and \
uber_model.get_backend().keras_version() == 2 and \
uber_model.get_backend().get_toolchain() == 'tensorflow' and \
sys.version_info < (3, 5):
pytest.skip('Occassional SIGSEGV')
uber_model.parse(jinja_engine)
uber_model.register_provider(uber_data)
uber_model.build()
trainer = Executor(model=uber_model, loss=loss, optimizer=optimizer)
trainer.compile()
trainer.train(provider=uber_data, stop_when={'epochs': 1})
def test_uber_train(self, uber_model, uber_data, jinja_engine, loss,
optimizer):
""" Tests that we can compile and train a diverse model.
"""
if uber_model.get_backend().get_name() == 'keras' and \
uber_model.get_backend().keras_version() == 2 and \
uber_model.get_backend().get_toolchain() == 'tensorflow' and \
sys.version_info < (3, 5):
pytest.skip('Occassional SIGSEGV')
uber_model.parse(jinja_engine)
uber_model.register_provider(uber_data)
uber_model.build()
trainer = Executor(
model=uber_model,
loss=loss,
optimizer=optimizer
)
trainer.compile()
trainer.train(provider=uber_data, stop_when={'epochs' : 1})