fix some dtype convert

Author: Difers

python/paddle/amp/auto_cast.py

@@ -529,6 +529,8 @@ def amp_guard(
         raise ValueError("level should be O0, OD, O1 or O2.")
 
     # check amp_dtype: float16 or bfloat16
+    if isinstance(dtype, paddle.base.core.DataType):
+        dtype = dtype.name
     dtype = dtype.lower()
     if enable:
         if dtype not in ['float16', 'bfloat16']:

python/paddle/nn/functional/activation.py

@@ -1753,8 +1753,9 @@ def log_softmax(
               [-12.31326640, -1.31326640 , -0.31326640 , -15.31326640],
               [-3.44018970 , -2.44018970 , -1.44018970 , -0.44018970 ]]])
     """
-
-    if (dtype is not None) and (not isinstance(dtype, core.VarDesc.VarType)):
+    if dtype is None:
+        dtype = x.dtype
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
     if in_dynamic_or_pir_mode():

python/paddle/sparse/unary.py

@@ -623,9 +623,13 @@ def cast(
     assert (
         in_dynamic_or_pir_mode()
     ), "Currently, Sparse API only support dynamic mode or pir mode."
-    if index_dtype and not isinstance(index_dtype, core.VarDesc.VarType):
+    if index_dtype and not isinstance(
+        index_dtype, (core.VarDesc.VarType, core.DataType)
+    ):
         index_dtype = convert_np_dtype_to_dtype_(index_dtype)
-    if value_dtype and not isinstance(value_dtype, core.VarDesc.VarType):
+    if value_dtype and not isinstance(
+        value_dtype, (core.VarDesc.VarType, core.DataType)
+    ):
         value_dtype = convert_np_dtype_to_dtype_(value_dtype)
     return _C_ops.sparse_cast(x, index_dtype, value_dtype)
 

python/paddle/tensor/creation.py

@@ -3274,9 +3274,8 @@ def tril_indices(
             [[1, 2, 2, 3, 3, 3],
              [0, 0, 1, 0, 1, 2]])
     """
-    if not isinstance(dtype, core.VarDesc.VarType):
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
         dtype = convert_np_dtype_to_dtype_(dtype)
-
     if not isinstance(row, int) or row < 0:
         raise TypeError("row should be a non-negative int")
 
@@ -3355,7 +3354,8 @@ def triu_indices(
             [[0 0 0 0 1 1 1 1 2 2 2 3 3]
              [0 1 2 3 0 1 2 3 1 2 3 2 3]]
     """
-    if not isinstance(dtype, core.VarDesc.VarType):
+
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
     if not isinstance(row, int) or row < 0:

python/paddle/tensor/math.py

@@ -4348,7 +4348,11 @@ def cumsum(
         flatten = True
     else:
         flatten = False
-    if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
+    if dtype is None:
+        dtype = x.dtype
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
+        dtype = convert_np_dtype_to_dtype_(dtype)
+    if dtype is not None and x.dtype != dtype:
         x = cast(x, dtype)
 
     if in_dynamic_or_pir_mode():
@@ -4396,7 +4400,11 @@ def cumsum_(
         flatten = True
     else:
         flatten = False
-    if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
+    if dtype is None:
+        dtype = x.dtype
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
+        dtype = convert_np_dtype_to_dtype_(dtype)
+    if dtype is not None and x.dtype != dtype:
         x = cast_(x, dtype)
 
     if in_dynamic_mode():
@@ -4652,8 +4660,12 @@ def logcumsumexp(
         flatten = True
     else:
         flatten = False
-    if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
-        x = cast(x, dtype)
+    if dtype is None:
+        dtype = x.dtype
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
+        dtype = convert_np_dtype_to_dtype_(dtype)
+    if dtype is not None and x.dtype != dtype:
+        x = cast_(x, dtype)
 
     if in_dynamic_or_pir_mode():
         if axis is None:
@@ -4753,9 +4765,12 @@ def cumprod(
     if dim is None:
         dim = -1
         x = x.flatten(0, len(x.shape) - 1)
-
-    if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
-        x = cast(x, dtype)
+    if dtype is None:
+        dtype = x.dtype
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
+        dtype = convert_np_dtype_to_dtype_(dtype)
+    if dtype is not None and x.dtype != dtype:
+        x = cast_(x, dtype)
 
     if in_dynamic_or_pir_mode():
         return _C_ops.cumprod(x, dim, False, False)
@@ -4802,8 +4817,11 @@ def cumprod_(
     if dim is None:
         dim = -1
         x = _C_ops.flatten_(x, 0, len(x.shape) - 1)
-
-    if dtype is not None and x.dtype != convert_np_dtype_to_dtype_(dtype):
+    if dtype is None:
+        dtype = x.dtype
+    if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
+        dtype = convert_np_dtype_to_dtype_(dtype)
+    if dtype is not None and x.dtype != dtype:
         x = cast_(x, dtype)
 
     if in_dynamic_mode():
@@ -5031,14 +5049,18 @@ def prod(
             [24.  , 1680.])
 
     """
+    if dtype is None:
+        dtype = x.dtype
     if dtype is not None:
+        if not isinstance(dtype, (core.VarDesc.VarType, core.DataType)):
+            dtype = convert_np_dtype_to_dtype_(dtype)
         check_dtype(
             dtype,
             'dtype',
             ['float32', 'float64', 'int32', 'int64', "float16", "uint16"],
             'prod',
         )
-        if x.dtype != convert_np_dtype_to_dtype_(dtype):
+        if x.dtype != dtype:
             x = cast(x, dtype)
 
     # axis is 0-size tensor.