Store data with default datatype in TensorContainer and remove limitation of datatype.

mindinsight/datavisual/common/exceptions.py

@@ -188,15 +188,6 @@ class ResponseDataExceedMaxValueError(MindInsightException):
                                                               http_code=400)
 
 
-class DataTypeError(MindInsightException):
-    """Data_type does not support."""
-    def __init__(self, error_detail):
-        error_msg = f'Data type does not support. Detail: {error_detail}'
-        super(DataTypeError, self).__init__(DataVisualErrors.DATA_TYPE_NOT_SUPPORT,
-                                            error_msg,
-                                            http_code=400)
-
-
 class TrainJobDetailNotInCacheError(MindInsightException):
     """Detail info of given train job is not in cache."""
     def __init__(self, error_detail="no detail provided."):

mindinsight/datavisual/data_transform/tensor_container.py

@@ -15,7 +15,6 @@
 """Tensor data container."""
 import numpy as np
 
-from mindinsight.datavisual.common.exceptions import DataTypeError
 from mindinsight.datavisual.common.log import logger
 from mindinsight.datavisual.data_transform.histogram import Histogram, Bucket
 from mindinsight.datavisual.proto_files import mindinsight_anf_ir_pb2 as anf_ir_pb2
@@ -253,19 +252,14 @@ class TensorContainer:
         Get ndarray of tensor.
 
         Args:
-            tensor (float16|float32|float64): tensor data.
+            tensor (mindinsight_anf_ir.proto.DataType): tensor data.
 
         Returns:
             numpy.ndarray, ndarray of tensor.
-
-        Raises:
-            DataTypeError, If data type of tensor is not among float16 or float32 or float64.
         """
         data_type_str = anf_ir_pb2.DataType.Name(self.data_type)
         if data_type_str == 'DT_FLOAT16':
             return np.array(tuple(tensor), dtype=np.float16).reshape(self.dims)
         if data_type_str == 'DT_FLOAT32':
             return np.array(tuple(tensor), dtype=np.float32).reshape(self.dims)
-        if data_type_str == 'DT_FLOAT64':
-            return np.array(tuple(tensor), dtype=np.float64).reshape(self.dims)
-        raise DataTypeError("Data type: {}.".format(data_type_str))
+        return np.array(tuple(tensor)).reshape(self.dims)

mindinsight/utils/constant.py

@@ -77,7 +77,6 @@ class DataVisualErrors(Enum):
     TENSOR_NOT_EXIST = 18
     MAX_RESPONSE_DATA_EXCEEDED_ERROR = 19
     STEP_TENSOR_DATA_NOT_IN_CACHE = 20
-    DATA_TYPE_NOT_SUPPORT = 21
 
 
 class ScriptConverterErrors(Enum):