[Fix] make `autocast` compatible with GTX1660 and make it more robust. (#344)

* fix amp

* fix amp

* make logic consistent with torch.autocast

* support multiple device

* fix as comment

* fix as comment

* avoid circle import

mmengine/runner/amp.py

@@ -5,8 +5,9 @@ from typing import Optional
 
 import torch
 
-from mmengine import print_log
+from ..device import get_device
-from mmengine.utils import TORCH_VERSION, digit_version
+from ..logging import print_log
+from ..utils import TORCH_VERSION, digit_version
 
 
 @contextmanager
@@ -74,7 +75,7 @@ def autocast(device_type: Optional[str] = None,
         # If pytorch version is between 1.5.0 and 1.10.0, the default value of
         # dtype for `torch.cuda.amp.autocast` is torch.float16.
         assert device_type == 'cuda' or device_type is None, (
-            'Pytorch version under 1.5.0 only supports running automatic '
+            'Pytorch version under 1.10.0 only supports running automatic '
             'mixed training with cuda')
         if dtype is not None or cache_enabled is not None:
             print_log(
@@ -96,19 +97,33 @@ def autocast(device_type: Optional[str] = None,
                     '`autocast` is only available in gpu mode')
 
     else:
-        if torch.cuda.is_available():
+        # Modified from https://github.com/pytorch/pytorch/blob/master/torch/amp/autocast_mode.py # noqa: E501
-            device_type = 'cuda' if device_type is None else device_type
+        # This code should update with the `torch.autocast`.
-        else:
+        if cache_enabled is None:
-            device_type = 'cpu' if device_type is None else device_type
+            cache_enabled = torch.is_autocast_cache_enabled()
+        device = get_device()
+        device_type = device if device_type is None else device_type
+
+        if device_type == 'cuda':
+            if dtype is None:
+                dtype = torch.get_autocast_gpu_dtype()
+
+            if dtype == torch.bfloat16 and not \
+                    torch.cuda.is_bf16_supported():
+                raise RuntimeError(
+                    'Current CUDA Device does not support bfloat16. Please '
+                    'switch dtype to float16.')
+
+        elif device_type == 'cpu':
+            if dtype is None:
+                dtype = torch.bfloat16
+            assert dtype == torch.bfloat16, (
+                'In CPU autocast, only support `torch.bfloat16` dtype')
+
+        else:
+            raise ValueError('User specified autocast device_type must be '
+                             F'cuda or cpu, but got {device_type}')
 
-        if digit_version(TORCH_VERSION) < digit_version('1.11.0'):
-            if dtype is not None and dtype != torch.bfloat16:
-                print_log(
-                    f'{dtype} must be `torch.bfloat16` with Pytorch '
-                    f'version: {TORCH_VERSION}',
-                    logger='current',
-                    level=logging.WARNING)
-            dtype = torch.bfloat16
         with torch.autocast(
                 device_type=device_type,
                 enabled=enabled,