!591 use default np.float64 to create ndarray to reduce error of calculation...

!591 use default np.float64 to create ndarray to reduce error of calculation precision in resample of tensor histogram
Merge pull request !591 from wangshuide/wsd0727

mindinsight/datavisual/data_transform/tensor_container.py

@@ -17,7 +17,6 @@ import numpy as np
 
 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
 from mindinsight.datavisual.utils.utils import calc_histogram_bins
 from mindinsight.utils.exceptions import ParamValueError
 
@@ -192,10 +191,8 @@ class TensorContainer:
         self._stats = get_statistics_from_tensor(self._np_array)
         original_buckets = calc_original_buckets(self._np_array, self._stats)
         self._count = sum(bucket.count for bucket in original_buckets)
-        # convert the type of max and min value to np.float64 so that it cannot overflow
-        # when calculating width of histogram.
-        self._max = np.float64(self._stats.max)
-        self._min = np.float64(self._stats.min)
+        self._max = self._stats.max
+        self._min = self._stats.min
         self._histogram = Histogram(tuple(original_buckets), self._max, self._min, self._count)
 
     @property
@@ -257,9 +254,4 @@ class TensorContainer:
         Returns:
             numpy.ndarray, ndarray of tensor.
         """
-        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)
         return np.array(tuple(tensor)).reshape(self.dims)