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# Copyright (c) ONNX Project Contributors
# SPDX-License-Identifier: Apache-2.0
import unittest
from typing import Any
import numpy as np
import parameterized
import onnx
from onnx import helper, numpy_helper
def bfloat16_to_float32(ival: int) -> Any:
if ival == 0x7FC0:
return np.float32(np.nan)
expo = ival >> 7
prec = ival - (expo << 7)
sign = expo & 256
powe = expo & 255
fval = float(prec * 2 ** (-7) + 1) * 2.0 ** (powe - 127)
if sign:
fval = -fval
return np.float32(fval)
def float8e4m3_to_float32(ival: int) -> Any:
if ival < 0 or ival > 255:
raise ValueError(f"{ival} is not a float8.")
if ival == 255:
return np.float32(-np.nan)
if ival == 127:
return np.float32(np.nan)
if (ival & 0x7F) == 0:
return np.float32(0)
sign = ival & 0x80
ival &= 0x7F
expo = ival >> 3
mant = ival & 0x07
powe = expo & 0x0F
if expo == 0:
powe -= 6
fraction = 0
else:
powe -= 7
fraction = 1
fval = float(mant / 8 + fraction) * 2.0**powe
if sign:
fval = -fval
return np.float32(fval)
def float8e5m2_to_float32(ival: int) -> Any:
if ival < 0 or ival > 255:
raise ValueError(f"{ival} is not a float8.")
if ival in (255, 254, 253):
return np.float32(-np.nan)
if ival in (127, 126, 125):
return np.float32(np.nan)
if ival == 252:
return -np.float32(np.inf)
if ival == 124:
return np.float32(np.inf)
if (ival & 0x7F) == 0:
return np.float32(0)
sign = ival & 0x80
ival &= 0x7F
expo = ival >> 2
mant = ival & 0x03
powe = expo & 0x1F
if expo == 0:
powe -= 14
fraction = 0
else:
powe -= 15
fraction = 1
fval = float(mant / 4 + fraction) * 2.0**powe
if sign:
fval = -fval
return np.float32(fval)
class TestNumpyHelper(unittest.TestCase):
def _test_numpy_helper_float_type(self, dtype: np.number) -> None:
a = np.random.rand(13, 37).astype(dtype)
tensor_def = numpy_helper.from_array(a, "test")
self.assertEqual(tensor_def.name, "test")
a_recover = numpy_helper.to_array(tensor_def)
np.testing.assert_equal(a, a_recover)
def _test_numpy_helper_int_type(self, dtype: np.number) -> None:
a = np.random.randint(
np.iinfo(dtype).min, np.iinfo(dtype).max, dtype=dtype, size=(13, 37)
)
tensor_def = numpy_helper.from_array(a, "test")
self.assertEqual(tensor_def.name, "test")
a_recover = numpy_helper.to_array(tensor_def)
np.testing.assert_equal(a, a_recover)
def test_float(self) -> None:
self._test_numpy_helper_float_type(np.float32)
def test_uint8(self) -> None:
self._test_numpy_helper_int_type(np.uint8)
def test_int8(self) -> None:
self._test_numpy_helper_int_type(np.int8)
def test_uint16(self) -> None:
self._test_numpy_helper_int_type(np.uint16)
def test_int16(self) -> None:
self._test_numpy_helper_int_type(np.int16)
def test_int32(self) -> None:
self._test_numpy_helper_int_type(np.int32)
def test_int64(self) -> None:
self._test_numpy_helper_int_type(np.int64)
def test_string(self) -> None:
a = np.array(["Amy", "Billy", "Cindy", "David"]).astype(object)
tensor_def = numpy_helper.from_array(a, "test")
self.assertEqual(tensor_def.name, "test")
a_recover = numpy_helper.to_array(tensor_def)
np.testing.assert_equal(a, a_recover)
def test_bool(self) -> None:
a = np.random.randint(2, size=(13, 37)).astype(bool)
tensor_def = numpy_helper.from_array(a, "test")
self.assertEqual(tensor_def.name, "test")
a_recover = numpy_helper.to_array(tensor_def)
np.testing.assert_equal(a, a_recover)
def test_float16(self) -> None:
self._test_numpy_helper_float_type(np.float32)
def test_complex64(self) -> None:
self._test_numpy_helper_float_type(np.complex64)
def test_complex128(self) -> None:
self._test_numpy_helper_float_type(np.complex128)
@parameterized.parameterized.expand(
[
(1,),
(0.100097656,),
(130048,),
(1.2993813e-5,),
(np.nan,),
(np.inf,),
]
)
def test_bfloat16_to_float32(self, f):
f32 = np.float32(f)
bf16 = helper.float32_to_bfloat16(f32)
assert isinstance(bf16, int)
f32_1 = numpy_helper.bfloat16_to_float32(np.array([bf16]))[0]
f32_2 = bfloat16_to_float32(bf16)
if np.isnan(f32):
assert np.isnan(f32_1)
assert np.isnan(f32_2)
else:
self.assertEqual(f32, f32_1)
self.assertEqual(f32, f32_2)
def test_float8e4m3_to_float32(self):
self.assertEqual(numpy_helper.float8e4m3_to_float32(int("1111110", 2)), 448)
self.assertEqual(numpy_helper.float8e4m3_to_float32(int("1000", 2)), 2 ** (-6))
self.assertEqual(numpy_helper.float8e4m3_to_float32(int("1", 2)), 2 ** (-9))
self.assertEqual(
numpy_helper.float8e4m3_to_float32(int("111", 2)), 0.875 * 2 ** (-6)
)
for f in [
0,
1,
-1,
0.5,
-0.5,
0.1015625,
-0.1015625,
2,
3,
-2,
-3,
448,
2 ** (-6),
2 ** (-9),
0.875 * 2 ** (-6),
np.nan,
]:
with self.subTest(f=f):
f32 = np.float32(f)
f8 = helper.float32_to_float8e4m3(f32)
assert isinstance(f8, int)
f32_1 = numpy_helper.float8e4m3_to_float32(np.array([f8]))[0]
f32_2 = float8e4m3_to_float32(f8)
if np.isnan(f32):
assert np.isnan(f32_1)
assert np.isnan(f32_2)
else:
self.assertEqual(f32, f32_1)
self.assertEqual(f32, f32_2)
@parameterized.parameterized.expand(
[
(0.00439453125, 0.00390625),
(0.005859375, 0.005859375),
(0.005759375, 0.005859375),
(0.0046875, 0.00390625),
(0.001953125, 0.001953125),
(0.0029296875, 0.00390625),
(0.002053125, 0.001953125),
(0.00234375, 0.001953125),
(0.0087890625, 0.0078125),
(0.001171875, 0.001953125),
(1.8131605, 1.875),
]
)
def test_float8e4m3_to_float32_round(self, val, expected):
f8 = helper.float32_to_float8e4m3(val)
f32 = numpy_helper.float8e4m3_to_float32(f8)
self.assertEqual(f32, expected)
def test_float8e5m2_to_float32(self):
self.assertEqual(numpy_helper.float8e5m2_to_float32(int("1111011", 2)), 57344)
self.assertEqual(numpy_helper.float8e5m2_to_float32(int("100", 2)), 2 ** (-14))
self.assertEqual(
numpy_helper.float8e5m2_to_float32(int("11", 2)), 0.75 * 2 ** (-14)
)
self.assertEqual(numpy_helper.float8e5m2_to_float32(int("1", 2)), 2 ** (-16))
self.assertTrue(np.isnan(numpy_helper.float8e5m2_to_float32(int("1111101", 2))))
self.assertTrue(np.isnan(numpy_helper.float8e5m2_to_float32(int("1111110", 2))))
self.assertTrue(np.isnan(numpy_helper.float8e5m2_to_float32(int("1111111", 2))))
self.assertTrue(
np.isnan(numpy_helper.float8e5m2_to_float32(int("11111101", 2)))
)
self.assertTrue(
np.isnan(numpy_helper.float8e5m2_to_float32(int("11111110", 2)))
)
self.assertTrue(
np.isnan(numpy_helper.float8e5m2_to_float32(int("11111111", 2)))
)
self.assertEqual(numpy_helper.float8e5m2_to_float32(int("1111100", 2)), np.inf)
self.assertEqual(
numpy_helper.float8e5m2_to_float32(int("11111100", 2)), -np.inf
)
for f in [
0,
0.0017089844,
20480,
14,
-3584,
np.nan,
]:
with self.subTest(f=f):
f32 = np.float32(f)
f8 = helper.float32_to_float8e5m2(f32)
assert isinstance(f8, int)
f32_1 = numpy_helper.float8e5m2_to_float32(np.array([f8]))[0]
f32_2 = float8e5m2_to_float32(f8)
if np.isnan(f32):
assert np.isnan(f32_1)
assert np.isnan(f32_2)
else:
self.assertEqual(f32, f32_1)
self.assertEqual(f32, f32_2)
def test_float8_e4m3fn_inf(self):
x = np.float32(np.inf)
to = helper.float32_to_float8e4m3(x)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, 448)
x = np.float32(np.inf)
to = helper.float32_to_float8e4m3(x, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
x = np.float32(-np.inf)
to = helper.float32_to_float8e4m3(x)
self.assertEqual(to & 0x80, 0x80)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, -448)
x = np.float32(-np.inf)
to = helper.float32_to_float8e4m3(x, saturate=False)
self.assertEqual(to & 0x80, 0x80)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
def test_float8_e4m3fnuz_inf(self):
x = np.float32(np.inf)
to = helper.float32_to_float8e4m3(x, uz=True)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertEqual(back, 240)
x = np.float32(np.inf)
to = helper.float32_to_float8e4m3(x, uz=True, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertTrue(np.isnan(back))
x = np.float32(-np.inf)
to = helper.float32_to_float8e4m3(x, uz=True)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertEqual(back, -240)
x = np.float32(-np.inf)
to = helper.float32_to_float8e4m3(x, uz=True, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertTrue(np.isnan(back))
def test_float8_e5m2_inf(self):
x = np.float32(np.inf)
to = helper.float32_to_float8e5m2(x)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertEqual(back, 57344)
x = np.float32(np.inf)
to = helper.float32_to_float8e5m2(x, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertTrue(np.isinf(back))
x = np.float32(-np.inf)
to = helper.float32_to_float8e5m2(x)
self.assertEqual(to & 0x80, 0x80)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertEqual(back, -57344)
x = np.float32(-np.inf)
to = helper.float32_to_float8e5m2(x, saturate=False)
self.assertEqual(to & 0x80, 0x80)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertTrue(np.isinf(back))
self.assertLess(back, 0)
def test_float8_e5m2fnuz_inf(self):
x = np.float32(np.inf)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertEqual(back, 57344)
x = np.float32(np.inf)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertTrue(np.isnan(back))
x = np.float32(-np.inf)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertEqual(back, -57344)
x = np.float32(-np.inf)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertTrue(np.isnan(back))
def test_float8_e4m3fn_out_of_range(self):
x = np.float32(1000000)
to = helper.float32_to_float8e4m3(x)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, 448)
x = np.float32(1000000)
to = helper.float32_to_float8e4m3(x, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
x = np.float32(-1000000)
to = helper.float32_to_float8e4m3(x)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, -448)
x = np.float32(-1000000)
to = helper.float32_to_float8e4m3(x, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
def test_float8_e4m3fnuz_out_of_range(self):
x = np.float32(1000000)
to = helper.float32_to_float8e4m3(x, uz=True)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertEqual(back, 240)
x = np.float32(1000000)
to = helper.float32_to_float8e4m3(x, uz=True, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertTrue(np.isnan(back))
x = np.float32(-1000000)
to = helper.float32_to_float8e4m3(x, uz=True)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertEqual(back, -240)
x = np.float32(-1000000)
to = helper.float32_to_float8e4m3(x, uz=True, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertTrue(np.isnan(back))
def test_float8_e5m2_out_of_range(self):
x = np.float32(1000000)
to = helper.float32_to_float8e5m2(x)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertEqual(back, 57344)
x = np.float32(1000000)
to = helper.float32_to_float8e5m2(x, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertTrue(np.isinf(back))
x = np.float32(-1000000)
to = helper.float32_to_float8e5m2(x)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertEqual(back, -57344)
x = np.float32(-1000000)
to = helper.float32_to_float8e5m2(x, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to)
self.assertTrue(np.isinf(back))
def test_float8_e5m2fnuz_out_of_range(self):
x = np.float32(1000000)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertEqual(back, 57344)
x = np.float32(1000000)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertTrue(np.isnan(back))
x = np.float32(-1000000)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertEqual(back, -57344)
x = np.float32(-1000000)
to = helper.float32_to_float8e5m2(x, fn=True, uz=True, saturate=False)
back = numpy_helper.float8e5m2_to_float32(to, fn=True, uz=True)
self.assertTrue(np.isnan(back))
def test_float8_e4m3fn_negative_zero(self):
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e4m3(x)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, 0)
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e4m3(x, saturate=False)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, 0)
def test_float8_e4m3fnuz_negative_zero(self):
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e4m3(x, uz=True)
self.assertEqual(to, 0)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertEqual(back, 0)
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e4m3(x, uz=True, saturate=False)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertEqual(back, 0)
self.assertEqual(to, 0)
def test_float8_e5m2_negative_zero(self):
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e5m2(x)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, 0)
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e5m2(x, saturate=False)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertEqual(back, 0)
def test_float8_e5m2fnuz_negative_zero(self):
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e5m2(x, fn=True, uz=True)
self.assertEqual(to, 0)
back = numpy_helper.float8e4m3_to_float32(to, fn=True, uz=True)
self.assertEqual(back, 0)
x = numpy_helper.float8e5m2_to_float32(0x80) # -0
to = helper.float32_to_float8e5m2(x, fn=True, uz=True, saturate=False)
self.assertEqual(to, 0)
back = numpy_helper.float8e4m3_to_float32(to, fn=True, uz=True)
self.assertEqual(back, 0)
def test_float8_e4m3fn_negative_nan(self):
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e4m3(x)
self.assertEqual(to, 255)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e4m3(x, saturate=False)
self.assertEqual(to, 255)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
def test_float8_e4m3fnuz_negative_nan(self):
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e4m3(x, uz=True)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertTrue(np.isnan(back))
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e4m3(x, uz=True, saturate=False)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to, uz=True)
self.assertTrue(np.isnan(back))
def test_float8_e5m2_negative_nan(self):
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e5m2(x)
self.assertEqual(to, 255)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e5m2(x, saturate=False)
self.assertEqual(to, 255)
back = numpy_helper.float8e4m3_to_float32(to)
self.assertTrue(np.isnan(back))
def test_float8_e5m2fnuz_negative_nan(self):
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e5m2(x, fn=True, uz=True)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to, fn=True, uz=True)
self.assertTrue(np.isnan(back))
x = numpy_helper.float8e5m2_to_float32(255) # -nan
to = helper.float32_to_float8e5m2(x, fn=True, uz=True, saturate=False)
self.assertEqual(to, 0x80)
back = numpy_helper.float8e4m3_to_float32(to, fn=True, uz=True)
self.assertTrue(np.isnan(back))
def test_from_dict_values_are_np_arrays_of_float(self):
map_proto = numpy_helper.from_dict({0: np.array(0.1), 1: np.array(0.9)})
self.assertIsInstance(map_proto, onnx.MapProto)
self.assertEqual(
numpy_helper.to_array(map_proto.values.tensor_values[0]), np.array(0.1)
)
self.assertEqual(
numpy_helper.to_array(map_proto.values.tensor_values[1]), np.array(0.9)
)
def test_from_dict_values_are_np_arrays_of_int(self):
map_proto = numpy_helper.from_dict({0: np.array(1), 1: np.array(9)})
self.assertIsInstance(map_proto, onnx.MapProto)
self.assertEqual(
numpy_helper.to_array(map_proto.values.tensor_values[0]), np.array(1)
)
self.assertEqual(
numpy_helper.to_array(map_proto.values.tensor_values[1]), np.array(9)
)
def test_from_dict_values_are_np_arrays_of_ints(self):
zero_array = np.array([1, 2])
one_array = np.array([9, 10])
map_proto = numpy_helper.from_dict({0: zero_array, 1: one_array})
self.assertIsInstance(map_proto, onnx.MapProto)
out_tensor = numpy_helper.to_array(map_proto.values.tensor_values[0])
self.assertEqual(out_tensor[0], zero_array[0])
self.assertEqual(out_tensor[1], zero_array[1])
out_tensor = numpy_helper.to_array(map_proto.values.tensor_values[1])
self.assertEqual(out_tensor[0], one_array[0])
self.assertEqual(out_tensor[1], one_array[1])
def test_from_dict_raises_type_error_when_values_are_not_np_arrays(self):
with self.assertRaises(TypeError):
# from_dict/from_array expects tensors to be numpy array's or similar.
numpy_helper.from_dict({0: 0.1, 1: 0.9})
def test_from_dict_differing_key_types(self):
with self.assertRaises(TypeError):
# Differing key types should raise a TypeError
numpy_helper.from_dict({0: np.array(0.1), 1.1: np.array(0.9)})
def test_from_dict_differing_value_types(self):
with self.assertRaises(TypeError):
# Differing value types should raise a TypeError
numpy_helper.from_dict({0: np.array(1), 1: np.array(0.9)})
if __name__ == "__main__":
unittest.main()
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