[Cleanup][A-12] clean some VarType for test

python/paddle/jit/translated_layer.py

@@ -503,7 +503,7 @@ def _preprocess(self, program_desc):
     def _append_scale_to_output(self, program):
         # 0. scale don't support bool output, we skip append scale for it
         for out_desc in self._output_descs:
-            if out_desc.dtype() == core.VarDesc.VarType.BOOL:
+            if out_desc.dtype() == paddle.bool:
                 return
 
         # 1. append scale & save var

python/paddle/static/amp/amp_nn.py

@@ -12,8 +12,8 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
+import paddle
 from paddle import _C_ops
-from paddle.base import core
 from paddle.base.data_feeder import check_type, check_variable_and_dtype
 from paddle.base.framework import Variable, in_dygraph_mode
 from paddle.base.layer_helper import LayerHelper
@@ -130,9 +130,9 @@ def update_loss_scaling(
             ['float16', 'float32', 'float64', 'uint16'],
             'update_loss_scaling',
         )
-        if e.dtype in [core.VarDesc.VarType.FP16, core.VarDesc.VarType.BF16]:
+        if e.dtype in [paddle.float16, paddle.bfloat16]:
             assert (
-                prev_loss_scaling.dtype == core.VarDesc.VarType.FP32
+                prev_loss_scaling.dtype == paddle.float32
             ), "The dtype of prev_loss_scaling should be float32 when the dtype of x is float16 or bfloat16."
         else:
             assert (

python/paddle/static/amp/bf16/amp_utils.py

@@ -19,6 +19,7 @@
 
 import numpy as np
 
+import paddle
 from paddle.base import core, framework, global_scope
 from paddle.base.log_helper import get_logger
 from paddle.base.wrapped_decorator import signature_safe_contextmanager
@@ -60,7 +61,7 @@ def _dtype_to_str(dtype):
     Args:
         dtype (VarType): Variable type.
     """
-    if dtype == core.VarDesc.VarType.BF16:
+    if dtype == paddle.bfloat16:
         return 'bf16'
     else:
         return 'fp32'
@@ -83,7 +84,7 @@ def _insert_cast_op(block, op, idx, src_dtype, dest_dtype):
     num_cast_ops = 0
 
     for in_name in op.input_names:
-        if src_dtype == core.VarDesc.VarType.FP32 and op.type in [
+        if src_dtype == paddle.float32 and op.type in [
             'batch_norm',
             'fused_bn_add_activation',
             'layer_norm',
@@ -120,10 +121,7 @@ def _insert_cast_op(block, op, idx, src_dtype, dest_dtype):
             else:
                 if op.has_attr('in_dtype'):
                     op._set_attr('in_dtype', dest_dtype)
-    if (
-        src_dtype == core.VarDesc.VarType.FP32
-        and dest_dtype == core.VarDesc.VarType.BF16
-    ):
+    if src_dtype == paddle.float32 and dest_dtype == paddle.bfloat16:
         for out_name in op.output_names:
             if (
                 op.type
@@ -135,7 +133,7 @@ def _insert_cast_op(block, op, idx, src_dtype, dest_dtype):
                 out_var = block.var(out_var_name)
                 if out_var.type not in _valid_types:
                     continue
-                if out_var.dtype == core.VarDesc.VarType.FP32:
+                if out_var.dtype == paddle.float32:
                     out_var.desc.set_dtype(core.VarDesc.VarType.BF16)
                     if op.has_attr('out_dtype'):
                         op._set_attr('out_dtype', core.VarDesc.VarType.BF16)
@@ -282,7 +280,7 @@ def cast_initializers_to_bf16(
 
             if change_op and are_post_ops_bf16(op_post_ops, keep_fp32_ops):
                 for out_var in op_out_vars:
-                    if out_var.dtype == core.VarDesc.VarType.FP32:
+                    if out_var.dtype == paddle.float32:
                         out_var.desc.set_dtype(core.VarDesc.VarType.BF16)
                     if (
                         to_bf16_var_names is not None
@@ -352,7 +350,7 @@ def cast_model_to_bf16(
                     if in_var is None or in_var.type not in _valid_types:
                         continue
 
-                    if in_var.dtype == core.VarDesc.VarType.FP32:
+                    if in_var.dtype == paddle.float32:
                         in_var.desc.set_dtype(core.VarDesc.VarType.BF16)
                         to_bf16_var_names.add(in_var_name)
 
@@ -386,7 +384,7 @@ def cast_model_to_bf16(
                     if out_var is None or out_var.type not in _valid_types:
                         continue
 
-                    if out_var.dtype == core.VarDesc.VarType.FP32:
+                    if out_var.dtype == paddle.float32:
                         out_var.desc.set_dtype(core.VarDesc.VarType.BF16)
 
                     _logger.debug(
@@ -397,7 +395,7 @@ def cast_model_to_bf16(
             for attr_name in ['in_dtype', 'out_dtype', 'dtype']:
                 if (
                     op.has_attr(attr_name)
-                    and op.attr(attr_name) == core.VarDesc.VarType.FP32
+                    and op.attr(attr_name) == paddle.float32
                 ):
                     op._set_attr(attr_name, core.VarDesc.VarType.BF16)
 
@@ -444,7 +442,7 @@ def cast_model_to_bf16(
                     out_var = block.vars.get(out_var_name)
                     if out_var is None or out_var.type not in _valid_types:
                         continue
-                    if out_var.dtype == core.VarDesc.VarType.BF16:
+                    if out_var.dtype == paddle.bfloat16:
                         out_var.desc.set_dtype(core.VarDesc.VarType.FP32)
                         post_ops = find_true_post_op(ops, op, out_var_name)
                         for post_op in post_ops:

python/paddle/static/amp/debugging.py

@@ -35,11 +35,11 @@ def update(self, dtype):
         if dtype is None:
             self.other_calls = self.other_calls + 1
         else:
-            if dtype == paddle.base.core.VarDesc.VarType.FP32:
+            if dtype == paddle.float32:
                 self.fp32_calls = self.fp32_calls + 1
-            elif dtype == paddle.base.core.VarDesc.VarType.FP16:
+            elif dtype == paddle.float16:
                 self.fp16_calls = self.fp16_calls + 1
-            elif dtype == paddle.base.core.VarDesc.VarType.BF16:
+            elif dtype == paddle.bfloat16:
                 self.bf16_calls = self.bf16_calls + 1
             else:
                 self.other_calls = self.other_calls + 1