Update251203 (#233)

tinygrad_repo/test/models/test_efficientnet.py

@@ -1,12 +1,10 @@
-import ast
-import pathlib
-import unittest
+import ast, pathlib, unittest
 
 import numpy as np
 from PIL import Image
 
-from tinygrad.helpers import getenv
-from tinygrad.tensor import Tensor
+from tinygrad import Tensor
+from tinygrad.helpers import getenv, CI
 from extra.models.efficientnet import EfficientNet
 from extra.models.vit import ViT
 from extra.models.resnet import ResNet50
@@ -40,19 +38,13 @@ def preprocess(img, new=False):
     img /= np.array([0.229, 0.224, 0.225]).reshape((1, -1, 1, 1))
   return img
 
+def _infer(model: EfficientNet, img):
+  with Tensor.train(False):
+    out = model.forward(Tensor(img)).argmax(axis=-1)
+  return out.tolist()
 
-def _infer(model: EfficientNet, img, bs=1):
-  old_training = Tensor.training
-  Tensor.training = False
-  img = preprocess(img)
-  # run the net
-  if bs > 1: img = img.repeat(bs, axis=0)
-  out = model.forward(Tensor(img))
-  Tensor.training = old_training
-  return _LABELS[np.argmax(out.numpy()[0])]
-
-chicken_img = Image.open(pathlib.Path(__file__).parent / 'efficientnet/Chicken.jpg')
-car_img = Image.open(pathlib.Path(__file__).parent / 'efficientnet/car.jpg')
+chicken_img = preprocess(Image.open(pathlib.Path(__file__).parent / 'efficientnet/Chicken.jpg'))
+car_img = preprocess(Image.open(pathlib.Path(__file__).parent / 'efficientnet/car.jpg'))
 
 class TestEfficientNet(unittest.TestCase):
   @classmethod
@@ -64,17 +56,20 @@ class TestEfficientNet(unittest.TestCase):
   def tearDownClass(cls):
     del cls.model
 
+  @unittest.skipIf(CI, "covered by test_chicken_car")
   def test_chicken(self):
-    label = _infer(self.model, chicken_img)
-    self.assertEqual(label, "hen")
-
-  def test_chicken_bigbatch(self):
-    label = _infer(self.model, chicken_img, 2)
-    self.assertEqual(label, "hen")
+    labels = _infer(self.model, chicken_img)
+    self.assertEqual(_LABELS[labels[0]], "hen")
 
+  @unittest.skipIf(CI, "covered by test_chicken_car")
   def test_car(self):
-    label = _infer(self.model, car_img)
-    self.assertEqual(label, "sports car, sport car")
+    labels = _infer(self.model, car_img)
+    self.assertEqual(_LABELS[labels[0]], "sports car, sport car")
+
+  def test_chicken_car(self):
+    labels = _infer(self.model, np.concat([chicken_img, car_img], axis=0))
+    self.assertEqual(_LABELS[labels[0]], "hen")
+    self.assertEqual(_LABELS[labels[1]], "sports car, sport car")
 
 class TestViT(unittest.TestCase):
   @classmethod
@@ -87,12 +82,12 @@ class TestViT(unittest.TestCase):
     del cls.model
 
   def test_chicken(self):
-    label = _infer(self.model, chicken_img)
-    self.assertEqual(label, "cock")
+    labels = _infer(self.model, chicken_img)
+    self.assertEqual(_LABELS[labels[0]], "cock")
 
   def test_car(self):
-    label = _infer(self.model, car_img)
-    self.assertEqual(label, "racer, race car, racing car")
+    labels = _infer(self.model, car_img)
+    self.assertEqual(_LABELS[labels[0]], "racer, race car, racing car")
 
 class TestResNet(unittest.TestCase):
   @classmethod
@@ -105,12 +100,12 @@ class TestResNet(unittest.TestCase):
     del cls.model
 
   def test_chicken(self):
-    label = _infer(self.model, chicken_img)
-    self.assertEqual(label, "hen")
+    labels = _infer(self.model, chicken_img)
+    self.assertEqual(_LABELS[labels[0]], "hen")
 
   def test_car(self):
-    label = _infer(self.model, car_img)
-    self.assertEqual(label, "sports car, sport car")
+    labels = _infer(self.model, car_img)
+    self.assertEqual(_LABELS[labels[0]], "sports car, sport car")
 
 if __name__ == '__main__':
   unittest.main()