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Fixes asarray for the Array API#25

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Merged
sdpython merged 2 commits intomainfromhypo
Jun 30, 2023
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38 changes: 32 additions & 6 deletions_unittests/ut_array_api/test_hypothesis_array_api.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -2,6 +2,7 @@
import warnings
from os import getenv
from functools import reduce
import numpy as np
from operator import mul
from hypothesis import given
from onnx_array_api.ext_test_case import ExtTestCase
Expand DownExpand Up@@ -89,24 +90,49 @@ def test_scalar_strategies(self):

args_np = []

xx = self.xps.arrays(dtype=dtypes["integer_dtypes"], shape=shapes(self.xps))
kws = array_api_kwargs(dtype=strategies.none() | self.xps.scalar_dtypes())

@given(
x=self.xps.arrays(dtype=dtypes["integer_dtypes"], shape=shapes(self.xps)),
kw=array_api_kwargs(dtype=strategies.none() | self.xps.scalar_dtypes()),
x=xx,
kw=kws,
)
def fct(x, kw):
def fctnp(x, kw):
asa1 = np.asarray(x)
asa2 = np.asarray(x, **kw)
self.assertEqual(asa1.shape, asa2.shape)
args_np.append((x, kw))

fct()
fctnp()
self.assertEqual(len(args_np), 100)

args_onxp = []

xshape = shapes(self.onxps)
xx = self.onxps.arrays(dtype=dtypes_onnx["integer_dtypes"], shape=xshape)
kw = array_api_kwargs(dtype=strategies.none() | self.onxps.scalar_dtypes())
kws = array_api_kwargs(dtype=strategies.none() | self.onxps.scalar_dtypes())

@given(x=xx, kw=kw)
@given(x=xx, kw=kws)
def fctonx(x, kw):
asa = np.asarray(x.numpy())
try:
asp = onxp.asarray(x)
except Exception as e:
raise AssertionError(f"asarray fails with x={x!r}, asp={asa!r}.") from e
try:
self.assertEqualArray(asa, asp.numpy())
except AssertionError as e:
raise AssertionError(
f"x={x!r} kw={kw!r} asa={asa!r}, asp={asp!r}"
) from e
if kw:
try:
asp2 = onxp.asarray(x, **kw)
except Exception as e:
raise AssertionError(
f"asarray fails with x={x!r}, kw={kw!r}, asp={asa!r}."
) from e
self.assertEqual(asp.shape, asp2.shape)
args_onxp.append((x, kw))

fctonx()
Expand Down
9 changes: 9 additions & 0 deletionsonnx_array_api/array_api/_onnx_common.py
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Original file line numberDiff line numberDiff line change
@@ -1,5 +1,10 @@
from typing import Any, Optional
import warnings
import numpy as np

with warnings.catch_warnings():
warnings.simplefilter("ignore")
from numpy.array_api._array_object import Array
from ..npx.npx_types import (
DType,
ElemType,
Expand DownExpand Up@@ -77,6 +82,10 @@ def asarray(
v = TEagerTensor(np.array(a, dtype=np.str_))
elif isinstance(a, list):
v = TEagerTensor(np.array(a))
elif isinstance(a, np.ndarray):
v = TEagerTensor(a)
elif isinstance(a, Array):
v = TEagerTensor(np.asarray(a))
else:
raise RuntimeError(f"Unexpected type {type(a)} for the first input.")
if dtype is not None:
Expand Down
29 changes: 24 additions & 5 deletionsonnx_array_api/npx/npx_numpy_tensors.py
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Original file line numberDiff line numberDiff line change
@@ -1,3 +1,4 @@
import warnings
from typing import Any, Callable, List, Optional, Tuple
import numpy as np
from onnx import ModelProto, TensorProto
Expand DownExpand Up@@ -221,13 +222,18 @@ def __bool__(self):
if self.shape == (0,):
return False
if len(self.shape) != 0:
raise ValueError(
f"Conversion to bool only works for scalar, not for {self!r}."
warnings.warn(
f"Conversion to bool only works for scalar, not for {self!r}, "
f"bool(...)={bool(self._tensor)}."
)
try:
return bool(self._tensor)
except ValueError as e:
raise ValueError(f"Unable to convert {self} to bool.") from e
return bool(self._tensor)

def __int__(self):
"Implicit conversion tobool."
"Implicit conversion toint."
if len(self.shape) != 0:
raise ValueError(
f"Conversion to bool only works for scalar, not for {self!r}."
Expand All@@ -249,7 +255,7 @@ def __int__(self):
return int(self._tensor)

def __float__(self):
"Implicit conversion tobool."
"Implicit conversion tofloat."
if len(self.shape) != 0:
raise ValueError(
f"Conversion to bool only works for scalar, not for {self!r}."
Expand All@@ -261,11 +267,24 @@ def __float__(self):
DType(TensorProto.BFLOAT16),
}:
raise TypeError(
f"Conversion toint only works for float scalar, "
f"Conversion tofloat only works for float scalar, "
f"not for dtype={self.dtype}."
)
return float(self._tensor)

def __iter__(self):
"""
The :epkg:`Array API` does not define this function (2022/12).
This method raises an exception with a better error message.
"""
warnings.warn(
f"Iterators are not implemented in the generic case. "
f"Every function using them cannot be converted into ONNX "
f"(tensors - {type(self)})."
)
for row in self._tensor:
yield self.__class__(row)


class JitNumpyTensor(NumpyTensor, JitTensor):
"""
Expand Down
5 changes: 3 additions & 2 deletionsonnx_array_api/npx/npx_tensors.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -35,8 +35,9 @@ def __iter__(self):
This method raises an exception with a better error message.
"""
raise ArrayApiError(
"Iterators are not implemented in the generic case. "
"Every function using them cannot be converted into ONNX."
f"Iterators are not implemented in the generic case. "
f"Every function using them cannot be converted into ONNX "
f"(tensors - {type(self)})."
)

@staticmethod
Expand Down
6 changes: 5 additions & 1 deletiononnx_array_api/npx/npx_types.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -59,12 +59,16 @@ def __eq__(self, dt: "DType") -> bool:
return False
if dt.__class__ is DType:
return self.code_ == dt.code_
if isinstance(dt, (int, bool, str)):
if isinstance(dt, (int, bool, str, float)):
return False
if dt is int:
return self.code_ == TensorProto.INT64
if dt is str:
return self.code_ == TensorProto.STRING
if dt is bool:
return self.code_ == TensorProto.BOOL
if dt is float:
return self.code_ == TensorProto.FLOAT64
if isinstance(dt, list):
return False
if dt in ElemType.numpy_map:
Expand Down
5 changes: 3 additions & 2 deletionsonnx_array_api/npx/npx_var.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -607,8 +607,9 @@ def __iter__(self):
This method raises an exception with a better error message.
"""
raise ArrayApiError(
"Iterators are not implemented in the generic case. "
"Every function using them cannot be converted into ONNX."
f"Iterators are not implemented in the generic case. "
f"Every function using them cannot be converted into ONNX "
f"(Var - {type(self)})."
)

def _binary_op(self, ov: "Var", op_name: str, **kwargs) -> "Var":
Expand Down
2 changes: 1 addition & 1 deletionrequirements-dev.txt
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Original file line numberDiff line numberDiff line change
Expand Up@@ -3,7 +3,7 @@ black
coverage
flake8
furo
hypothesis<6.80.0
hypothesis
isort
joblib
lightgbm
Expand Down
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