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!1080 Fix dtype check in infer_dtype() function of comm_ops.py 

Merge pull request !1080 from zhouyuanshen/master
This commit is contained in:
mindspore-ci-bot 2020-05-14 16:47:05 +08:00 committed by Gitee
parent 40beecc3a6 b7039a5797
commit 331ca249ef
1 changed files with 7 additions and 10 deletions
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17
mindspore/ops/operations/comm_ops.py
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@ -39,6 +39,8 @@ class ReduceOp:
PROD = "prod"
target_dtypes = (mstype.int8, mstype.int32, mstype.float16, mstype.float32)
class AllReduce(PrimitiveWithInfer):
"""
Reduces the tensor data across all devices in such a way that all devices will get the same final result.
@ -102,8 +104,7 @@ class AllReduce(PrimitiveWithInfer):
return x_shape
def infer_dtype(self, x_dtype):
if x_dtype.element_type() == mstype.bool_:
raise TypeError("AllReduce does not support 'Bool' as the dtype of input!")
validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
return x_dtype
@ -161,8 +162,7 @@ class AllGather(PrimitiveWithInfer):
return x_shape
def infer_dtype(self, x_dtype):
if x_dtype.element_type() == mstype.bool_:
raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
return x_dtype
def __call__(self, tensor):
@ -219,8 +219,7 @@ class ReduceScatter(PrimitiveWithInfer):
return x_shape
def infer_dtype(self, x_dtype):
if x_dtype.element_type() == mstype.bool_:
raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
return x_dtype
def __call__(self, tensor):
@ -279,8 +278,7 @@ class Broadcast(PrimitiveWithInfer):
if not isinstance(x_dtype, tuple):
raise TypeError(f"{self.name}'s input should be a tuple!")
for _ele in x_dtype:
if _ele.element_type() == mstype.bool_:
raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
validator.check_tensor_type_same({'x': _ele}, target_dtypes, self.name)
return x_dtype
@ -322,8 +320,7 @@ class _AlltoAll(PrimitiveWithInfer):
return x_shape
def infer_dtype(self, x_dtype):
if x_dtype.element_type() == mstype.bool_:
raise TypeError(f"{self.name} does not support 'Bool' as the dtype of input!")
validator.check_tensor_type_same({'x': x_dtype}, target_dtypes, self.name)
return x_dtype
def __call__(self, tensor):