fix failed tests in numpy2.0 (#65627)

risemeup1 · web-flow · commit 18dd803d84e8 · 2024-07-02T19:41:32.000+08:00
* fix numpy bug

* fix

* fix

* fix=document_fix

* fix,test=document_fix
diff --git a/python/paddle/vision/transforms/functional_cv2.py b/python/paddle/vision/transforms/functional_cv2.py
@@ -405,12 +405,11 @@ def adjust_hue(img, hue_factor):
     img = img.astype(np.uint8)
     hsv_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV_FULL)
     h, s, v = cv2.split(hsv_img)
-
-    alpha = np.random.uniform(hue_factor, hue_factor)
-    h = h.astype(np.uint8)
-    # uint8 addition take cares of rotation across boundaries
-    with np.errstate(over="ignore"):
-        h += np.uint8(alpha * 255)
+    alpha = hue_factor
+    h = h.astype(np.int32)  # Convert to int32 to prevent overflow
+    # uint8 addition takes care of rotation across boundaries
+    h = (h + int(alpha * 255)) % 256  # Ensure values are within [0, 255]
+    h = h.astype(np.uint8)  # Convert back to uint8
     hsv_img = cv2.merge([h, s, v])
     return cv2.cvtColor(hsv_img, cv2.COLOR_HSV2BGR_FULL).astype(dtype)
 
diff --git a/python/paddle/vision/transforms/functional_pil.py b/python/paddle/vision/transforms/functional_pil.py
@@ -66,7 +66,7 @@ def to_tensor(pic, data_format='CHW'):
         img = paddle.to_tensor(np.array(pic, np.int32, copy=False))
     elif pic.mode == 'I;16':
         # cast and reshape not support int16
-        img = paddle.to_tensor(np.array(pic, np.int32, copy=False))
+        img = paddle.to_tensor(np.asarray(pic, np.int32, copy=False))
     elif pic.mode == 'F':
         img = paddle.to_tensor(np.array(pic, np.float32, copy=False))
     elif pic.mode == '1':
@@ -402,11 +402,10 @@ def adjust_hue(img, hue_factor):
     h, s, v = img.convert('HSV').split()
 
     np_h = np.array(h, dtype=np.uint8)
-    # uint8 addition take cares of rotation across boundaries
-    with np.errstate(over='ignore'):
-        np_h += np.uint8(hue_factor * 255)
+    np_h = np_h.astype(np.int16)
+    np_h = (np_h + int(hue_factor * 255)) % 256
+    np_h = np_h.astype(np.uint8)
     h = Image.fromarray(np_h, 'L')
-
     img = Image.merge('HSV', (h, s, v)).convert(input_mode)
     return img
 
diff --git a/python/unittest_py/requirements.txt b/python/unittest_py/requirements.txt
@@ -8,7 +8,8 @@ hypothesis
 opencv-python>= 4.10.0.84
 visualdl==2.5.3
 paddle2onnx>=0.9.6
-scipy>=1.6, !=1.7.2, !=1.7.3
+scipy>=1.6, !=1.7.2, !=1.7.3 ; platform_system == "Windows"
+scipy>=1.13 ; platform_system != "Windows"
 prettytable
 distro
 autograd==1.4
diff --git a/test/legacy_test/test_transforms.py b/test/legacy_test/test_transforms.py
@@ -930,13 +930,14 @@ def test_to_tensor(self):
         pil_img = Image.fromarray(np_img).convert('I')
         pil_tensor = F.to_tensor(pil_img)
 
-        pil_img = Image.fromarray(np_img).convert('I;16')
+        pil_img_16bit = Image.new('I;16', pil_img.size)
+        pil_img_16bit.paste(pil_img)
         pil_tensor = F.to_tensor(pil_img)
 
         pil_img = Image.fromarray(np_img).convert('F')
         pil_tensor = F.to_tensor(pil_img)
 
-        pil_img = Image.fromarray(np_img).convert('1')
+        pil_img = Image.fromarray(np_img).convert('L')
         pil_tensor = F.to_tensor(pil_img)
 
         pil_img = Image.fromarray(np_img).convert('YCbCr')
diff --git a/test/xpu/test_unique_op_xpu.py b/test/xpu/test_unique_op_xpu.py
@@ -116,7 +116,8 @@ def init_config(self):
                 return_counts=True,
                 axis=None,
             )
-            inverse = inverse.flatten()
+            if np.__version__.startswith('2.'):
+                inverse = inverse.flatten()
             self.attrs = {
                 'dtype': int(core.VarDesc.VarType.INT64),
                 "return_index": True,
@@ -161,7 +162,8 @@ def init_config(self):
                 return_counts=True,
                 axis=1,
             )
-            inverse = inverse.flatten()
+            if np.__version__.startswith('2.'):
+                inverse = inverse.flatten()
             self.attrs = {
                 'dtype': int(core.VarDesc.VarType.INT32),
                 "return_index": True,
@@ -190,8 +192,8 @@ def init_config(self):
                 return_counts=True,
                 axis=0,
             )
-            inverse = inverse.flatten()
-
+            if np.__version__.startswith('2.'):
+                inverse = inverse.flatten()
             self.attrs = {
                 'dtype': int(core.VarDesc.VarType.INT32),
                 "return_index": True,
@@ -220,7 +222,8 @@ def init_config(self):
                 return_counts=True,
                 axis=-1,
             )
-            inverse = inverse.flatten()
+            if np.__version__.startswith('2.'):
+                inverse = inverse.flatten()
             self.attrs = {
                 'dtype': int(core.VarDesc.VarType.INT32),
                 "return_index": True,
