From de5c69c4c98e8ec6bf0304ab74a510ed5a90e094 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Szymon=20O=C5=BC=C3=B3g?=
 <58388001+SzymonOzog@users.noreply.github.com>
Date: Sat, 25 May 2024 16:12:40 +0200
Subject: [PATCH] Unify test_dtype naming conventions (#4730)

---
 test/test_dtype.py | 22 +++++++++++-----------
 1 file changed, 11 insertions(+), 11 deletions(-)

diff --git a/test/test_dtype.py b/test/test_dtype.py
index 689be1d7..0240d134 100644
--- a/test/test_dtype.py
+++ b/test/test_dtype.py
@@ -189,7 +189,7 @@ class TestBFloat16DTypeCast(unittest.TestCase):
     converted = random_values.cast(dtypes.bfloat16).cast(dtypes.float32)
     np.testing.assert_allclose(converted.numpy(), random_values.cast(dtypes.float32).numpy(), rtol=1e-2, atol=1e-3)
 
-class TestHalfDtype(TestDType): DTYPE = dtypes.half
+class TestHalfDType(TestDType): DTYPE = dtypes.half
 
 class TestFloatDType(TestDType):
   DTYPE = dtypes.float
@@ -198,7 +198,7 @@ class TestFloatDType(TestDType):
     _test_op(lambda: Tensor([-0.9, -0.3, 1.2], dtype=dtypes.float32).cast(dtypes.uint32), dtypes.uint32,
              [0, 0, 1])
 
-class TestDoubleDtype(TestDType):
+class TestDoubleDType(TestDType):
   DTYPE = dtypes.double
   @unittest.skipIf((CI and Device.DEFAULT in {"CUDA", "NV"}) or getenv("PTX"), "conversion not supported on CUDACPU and PTX")  # TODO: why not?
   def test_float64_increased_precision(self):
@@ -222,7 +222,7 @@ class TestDoubleDtype(TestDType):
              dtypes.float32, [float('inf'), 3.4e38, 1, 0])
 
 
-class TestInt8Dtype(TestDType):
+class TestInt8DType(TestDType):
   DTYPE = dtypes.int8
   @unittest.skipIf(getenv("CUDA",0)==1 or getenv("PTX", 0)==1, "cuda saturation works differently")
   def test_int8_to_uint8_negative(self):
@@ -231,7 +231,7 @@ class TestInt8Dtype(TestDType):
   def test_int8_to_uint16_negative(self):
     _test_op(lambda: Tensor([-1, -2, -3, -4], dtype=dtypes.int8).cast(dtypes.uint16), dtypes.uint16, [2**16-1, 2**16-2, 2**16-3, 2**16-4])
 
-class TestUint8Dtype(TestDType):
+class TestUint8DType(TestDType):
   DTYPE = dtypes.uint8
   @unittest.skipIf(getenv("CUDA",0)==1 or getenv("PTX", 0)==1, "cuda saturation works differently")
   def test_uint8_to_int8_overflow(self):
@@ -253,21 +253,21 @@ class TestBitCast(unittest.TestCase):
     b = a.bitcast(dtypes.float32)
     assert b.numpy()[0,0] == 1.
 
-class TestInt16Dtype(TestDType): DTYPE = dtypes.int16
+class TestInt16DType(TestDType): DTYPE = dtypes.int16
 
-class TestUint16Dtype(TestDType):
+class TestUint16DType(TestDType):
   DTYPE = dtypes.uint16
 
   def test_uint16_to_int8_overflow(self):
     _test_op(lambda: Tensor([2**16-1, 2**16-2, 1, 0], dtype=dtypes.uint16).cast(dtypes.int8), dtypes.int8, [-1, -2, 1, 0])
 
-class TestInt32Dtype(TestDType): DTYPE = dtypes.int32
-class TestUint32Dtype(TestDType): DTYPE = dtypes.uint32
+class TestInt32DType(TestDType): DTYPE = dtypes.int32
+class TestUint32DType(TestDType): DTYPE = dtypes.uint32
 
-class TestInt64Dtype(TestDType): DTYPE = dtypes.int64
-class TestUint64Dtype(TestDType): DTYPE = dtypes.uint64
+class TestInt64DType(TestDType): DTYPE = dtypes.int64
+class TestUint64DType(TestDType): DTYPE = dtypes.uint64
 
-class TestBoolDtype(TestDType): DTYPE = dtypes.bool
+class TestBoolDType(TestDType): DTYPE = dtypes.bool
 
 class TestImageDType(unittest.TestCase):
   def test_image_scalar(self):