delete bf16 of cross entropy (#53922)

* delete bf16 of cross entropy

* delete bf16 of cross entropy

paddle/phi/kernels/gpu/cross_entropy_grad_kernel.cu

@@ -297,8 +297,7 @@ PD_REGISTER_KERNEL(cross_entropy_with_softmax_grad,
                    phi::CrossEntropyWithSoftmaxGradKernel,
                    float,
                    double,
-                   phi::dtype::float16,
-                   phi::dtype::bfloat16) {}
+                   phi::dtype::float16) {}
 #else
 PD_REGISTER_KERNEL(cross_entropy_with_softmax_grad,
                    GPU,

paddle/phi/kernels/gpu/cross_entropy_kernel.cu

@@ -1479,8 +1479,7 @@ PD_REGISTER_KERNEL(cross_entropy_with_softmax,
                    phi::CrossEntropyWithSoftmaxKernel,
                    float,
                    double,
-                   phi::dtype::float16,
-                   phi::dtype::bfloat16) {}
+                   phi::dtype::float16) {}
 #else
 PD_REGISTER_KERNEL(cross_entropy_with_softmax,
                    GPU,

python/paddle/fluid/tests/unittests/test_softmax_with_cross_entropy_op.py

@@ -15,7 +15,7 @@
 import unittest
 
 import numpy as np
-from eager_op_test import OpTest, convert_float_to_uint16, paddle_static_guard
+from eager_op_test import OpTest, paddle_static_guard
 from test_softmax_op import stable_softmax
 
 import paddle
@@ -918,62 +918,6 @@ class TestSoftmaxWithCrossEntropyOpBoundary1(TestSoftmaxWithCrossEntropyOp):
         self.use_softmax = True
 
 
-@unittest.skipIf(
-    not core.is_compiled_with_cuda()
-    or not core.is_bfloat16_supported(core.CUDAPlace(0)),
-    "core is not compiled with CUDA and not support the bfloat16",
-)
-class TestSoftmaxWithCrossEntropyOpBF16(TestSoftmaxWithCrossEntropyOp):
-    def setUp(self):
-        self.initParams()
-        self.op_type = "softmax_with_cross_entropy"
-        self.dtype = np.uint16
-
-        # NOTE: numpy bf16 have very low accuracy, use float32 for numpy check.
-        date_type = np.float32
-        logits = getattr(
-            self,
-            "logits",
-            np.random.uniform(0.1, 1.0, self.shape).astype(date_type),
-        )
-        softmax = np.apply_along_axis(stable_softmax, self.axis, logits)
-
-        axis_dim = self.shape[self.axis]
-        self.shape[self.axis] = 1
-        labels = np.random.randint(0, axis_dim, self.shape, dtype="int64")
-
-        loss = cross_entropy(softmax, labels, self.soft_label, self.axis)
-
-        self.inputs = {
-            "Logits": convert_float_to_uint16(logits),
-            "Label": labels,
-        }
-        self.outputs = {
-            "Softmax": convert_float_to_uint16(softmax),
-            "Loss": convert_float_to_uint16(loss),
-        }
-        self.attrs = {
-            "numeric_stable_mode": self.numeric_stable_mode,
-            "soft_label": self.soft_label,
-        }
-        if self.axis != -1:
-            self.attrs['axis'] = self.axis
-
-    def test_check_output(self):
-        place = core.CUDAPlace(0)
-        if self.python_api is not None:
-            self.check_output_with_place(place)
-        self.check_output_with_place(place, atol=1e-2)
-
-    def test_check_grad(self):
-        place = core.CUDAPlace(0)
-        if self.python_api is not None:
-            self.check_grad_with_place(place, ["Logits"], "Loss")
-        self.check_grad_with_place(
-            place, ["Logits"], "Loss", max_relative_error=0.1
-        )
-
-
 class TestSoftmaxWithCrossEntropyOpError(unittest.TestCase):
     def test_errors(self):
         with program_guard(Program(), Program()):