[CI] Check test if the GenerationTesterMixin inheritance is correct 🐛 🔫 (#36180)

tests/generation/test_utils.py

@@ -19,6 +19,7 @@ import copy
 import datetime
 import gc
 import inspect
+import random
 import tempfile
 import unittest
 import warnings
@@ -48,8 +49,6 @@ from transformers.testing_utils import (
 )
 from transformers.utils import is_ipex_available
 
-from ..test_modeling_common import floats_tensor, ids_tensor
-
 
 if is_torch_available():
     import torch
@@ -2786,6 +2785,43 @@ class UtilsFunctionsTest(unittest.TestCase):
         self.assertTrue(last_token_counts[8] > last_token_counts[3])
 
 
+global_rng = random.Random()
+
+
+# Copied from tests.test_modeling_common.ids_tensor
+def ids_tensor(shape, vocab_size, rng=None, name=None):
+    #  Creates a random int32 tensor of the shape within the vocab size
+    if rng is None:
+        rng = global_rng
+
+    total_dims = 1
+    for dim in shape:
+        total_dims *= dim
+
+    values = []
+    for _ in range(total_dims):
+        values.append(rng.randint(0, vocab_size - 1))
+
+    return torch.tensor(data=values, dtype=torch.long, device=torch_device).view(shape).contiguous()
+
+
+# Copied from tests.test_modeling_common.floats_tensor
+def floats_tensor(shape, scale=1.0, rng=None, name=None):
+    """Creates a random float32 tensor"""
+    if rng is None:
+        rng = global_rng
+
+    total_dims = 1
+    for dim in shape:
+        total_dims *= dim
+
+    values = []
+    for _ in range(total_dims):
+        values.append(rng.random() * scale)
+
+    return torch.tensor(data=values, dtype=torch.float, device=torch_device).view(shape).contiguous()
+
+
 @pytest.mark.generate
 @require_torch
 class GenerationIntegrationTests(unittest.TestCase):