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Remove errornous checking for converting float64 to float32. In reality the slight difference by downcasting is totally fine. (#1935)

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This commit is contained in:
maniarathi
2020-10-19 10:31:36 -07:00
committed by GitHub
parent 6a741956e1
commit 377e4bccaa
1 changed files with 7 additions and 16 deletions
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23
server/common/utils/type_conversion_utils.py
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@@ -88,24 +88,15 @@ def get_schema_type_hint_from_dtype(dtype, array_values=None):
def can_cast_to_float32(dtype, array_values):
"""
A dtype can be cast to float32 if it is a float type and converting it to float32 presents the same output as the
original values. Note that NaNs fail equality (i.e. np.NaN != np.NaN) so we use np.testing.assert_equal to ensure
that the arrays are equal minus NaNs.
Optimistically returns True signifying that a type downcast to float32 is possible whenever the incoming type is
a float.
We also handle a special case here where the array is a Series object with integer categorical values AND NaNs.
Since NaNs are floating points in numpy, we upcast the integer array to float32.
Since NaNs are floating points in numpy, we upcast the integer array to float32 and return True.
"""
if dtype.kind == "f":
# Try to convert the array to float32
converted_float32_values = array_values.to_numpy(np.float32)
original_values = array_values.to_numpy()
# Verify that the two arrays are equal except for NaNs (which will equate to be unequal).
if not ((converted_float32_values != original_values) == np.isnan(original_values)).all():
return False
if dtype != np.float32:
if not np.can_cast(dtype, np.float32):
logging.warning(f"Type {dtype.name} will be converted to 32 bit float and may lose precision.")
return True
@@ -138,9 +129,9 @@ def can_cast_to_int32(dtype, array_values=None):
return True
ii32 = np.iinfo(np.int32)
if (
not ordered_array_values.empty
and (ordered_array_values.min() >= ii32.min and ordered_array_values.max() <= ii32.max)
or ordered_array_values.empty
not ordered_array_values.empty
and (ordered_array_values.min() >= ii32.min and ordered_array_values.max() <= ii32.max)
or ordered_array_values.empty
):
return True
return False