cvmodelz/tests/model_tests/pretrained_tests.py

import io
import numpy as np
import unittest
import test_utils

from chainer.serializers import npz
from contextlib import contextmanager


from cvmodelz.models.pretrained import *
from cvmodelz.models import ModelFactory

class PretrainedTests(unittest.TestCase):

	@contextmanager
	def mem_file(self) -> io.BytesIO:
		yield io.BytesIO()

	def load_for_finetune(self, key):

		model = ModelFactory.new(key, n_classes=1000)
		new_model = ModelFactory.new(key, n_classes=1000)

		self.assertTrue(test_utils.is_any_different(model, new_model))

		with self.mem_file() as f:
			model.save(f)
			f.seek(0)
			new_model.load_for_finetune(f, n_classes=200, strict=True)

		self.assertTrue(test_utils.is_all_equal(model, new_model))

	def load_for_inference(self, key):

		model = ModelFactory.new(key, n_classes=200)
		new_model = ModelFactory.new(key, n_classes=1000)

		self.assertTrue(test_utils.is_any_different(model, new_model))

		with self.mem_file() as f:
			model.save(f)
			f.seek(0)
			new_model.load_for_inference(f, n_classes=200, strict=True)

		self.assertTrue(test_utils.is_all_equal(model, new_model, strict=True))



test_utils.add_tests(PretrainedTests.load_for_finetune,
	model_list=ModelFactory.get_models(["chainercv2", "cvmodelz"]))

test_utils.add_tests(PretrainedTests.load_for_inference,
	model_list=ModelFactory.get_models(["chainercv2", "cvmodelz"]))