modified the python/paddle/amp/auto_cast.py to fix bug (#55364)

python/paddle/amp/auto_cast.py

@@ -370,6 +370,7 @@ def amp_guard(
                 "For float16, amp only support NVIDIA GPU with Compute Capability 7.0 or higher, current GPU is: %s, with Compute Capability: %d.%d."
                 % (paddle.device.cuda.get_device_name(), prop[0], prop[1])
             )
+            enable = False
         elif (dtype == 'bfloat16') and not _is_gpu_bfloat16_supported():
             prop = paddle.device.cuda.get_device_capability()
             cuda_version = paddle.version.cuda()
@@ -382,6 +383,7 @@ def amp_guard(
                     cuda_version,
                 )
             )
+            enable = False
 
     amp_dtype = dtype
     amp_global_state().amp_dtype = amp_dtype
@@ -572,6 +574,46 @@ def amp_decorate(
         else:
             return models, optimizers
 
+    # check tracer
+    tracer = _dygraph_tracer()
+    if not tracer:
+        raise ValueError(
+            "current_tracer is None, maybe it is not in imperative mode."
+        )
+
+    # check device_type:
+    if not (
+        tracer._expected_place.is_gpu_place()
+        or tracer._expected_place.is_xpu_place()
+        or tracer._expected_place.is_custom_place()
+    ):
+        if optimizers is None:
+            return models
+        else:
+            return models, optimizers
+    # For xpu:
+    if tracer._expected_place.is_xpu_place() and (dtype == 'bfloat16'):
+        if optimizers is None:
+            return models
+        else:
+            return models, optimizers
+    # For custom device:
+    if tracer._expected_place.is_custom_place() and (dtype == 'bfloat16'):
+        if optimizers is None:
+            return models
+        else:
+            return models, optimizers
+    # For gpu float16: Compute Capability should >= 7.
+    # For gpu bfloat16: Compute Capability should >= 8 & CUDA Version should >= 11.
+    if tracer._expected_place.is_gpu_place():
+        if (dtype == 'float16' and not _is_gpu_float16_supported()) or (
+            dtype == 'bfloat16' and not _is_gpu_bfloat16_supported()
+        ):
+            if optimizers is None:
+                return models
+            else:
+                return models, optimizers
+
     models_is_list = False
     if isinstance(models, paddle.nn.Layer):
         models_is_list = False