def make_attribute(
key, # type: Text
value, # type: Any
doc_string=None # type: Optional[Text]
): # type: (...) -> AttributeProto
"""Makes an AttributeProto based on the value type."""
attr = AttributeProto()
attr.name = key
if doc_string:
attr.doc_string = doc_string
is_iterable = isinstance(value, collections.Iterable)
bytes_or_false = _to_bytes_or_false(value)
# First, singular cases
# float
if isinstance(value, float):
attr.f = value
attr.type = AttributeProto.FLOAT
# integer
elif isinstance(value, numbers.Integral):
attr.i = cast(int, value)
attr.type = AttributeProto.INT
# string
elif bytes_or_false:
assert isinstance(bytes_or_false, bytes)
attr.s = bytes_or_false
attr.type = AttributeProto.STRING
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
attr.type = AttributeProto.TENSOR
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
attr.type = AttributeProto.GRAPH
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, float) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(byte_array):
attr.strings.extend(cast(List[bytes], byte_array))
attr.type = AttributeProto.STRINGS
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
attr.type = AttributeProto.TENSORS
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
attr.type = AttributeProto.GRAPHS
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type.")
else:
raise ValueError(
'Value "{}" is not valid attribute data type.'.format(value))
return attr
def make_attribute(
key, # type: Text
value, # type: Any
doc_string=None # type: Optional[Text]
): # type: (...) -> AttributeProto
"""Makes an AttributeProto based on the value type."""
attr = AttributeProto()
attr.name = key
if doc_string:
attr.doc_string = doc_string
is_iterable = isinstance(value, collections.Iterable)
bytes_or_false = _to_bytes_or_false(value)
# First, singular cases
# float
if isinstance(value, float):
attr.f = value
attr.type = AttributeProto.FLOAT
# integer
elif isinstance(value, numbers.Integral):
attr.i = cast(int, value)
attr.type = AttributeProto.INT
# string
elif bytes_or_false:
assert isinstance(bytes_or_false, bytes)
attr.s = bytes_or_false
attr.type = AttributeProto.STRING
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
attr.type = AttributeProto.TENSOR
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
attr.type = AttributeProto.GRAPH
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, float) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(byte_array):
attr.strings.extend(cast(List[bytes], byte_array))
attr.type = AttributeProto.STRINGS
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
attr.type = AttributeProto.TENSORS
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
attr.type = AttributeProto.GRAPHS
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type.")
else:
raise ValueError(
'Value "{}" is not valid attribute data type.'.format(value))
return attr
def make_attribute(key: str, value) -> IAttributeProto:
attr = AttributeProto()
attr.name = key
is_iterable = isinstance(value, Iterable)
bytes_or_false = _to_bytes_or_false(value)
# First, singular cases
# float
if isinstance(value, float):
attr.f = value
# integer
elif isinstance(value, numbers.Integral):
attr.i = value
# string
elif bytes_or_false:
attr.s = bytes_or_false
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, float) for v in value):
attr.floats.extend(value)
elif all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
elif all(byte_array):
attr.strings.extend(byte_array)
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type.")
else:
raise ValueError(
'Value "{}" is not valid attribute data type.'.format(value))
return attr
def test_is_attr_legal(self): # type: () -> None
# no name, no field
attr = AttributeProto()
self.assertRaises(checker.ValidationError, checker.check_attribute, attr)
# name, but no field
attr = AttributeProto()
attr.name = "test"
self.assertRaises(checker.ValidationError, checker.check_attribute, attr)
# name, with two fields
attr = AttributeProto()
attr.name = "test"
attr.f = 1.0
attr.i = 2
self.assertRaises(checker.ValidationError, checker.check_attribute, attr)
def test_is_attr_legal(self): # type: () -> None
# no name, no field
attr = AttributeProto()
self.assertRaises(checker.ValidationError, checker.check_attribute, attr)
# name, but no field
attr = AttributeProto()
attr.name = "test"
self.assertRaises(checker.ValidationError, checker.check_attribute, attr)
# name, with two fields
attr = AttributeProto()
attr.name = "test"
attr.f = 1.0
attr.i = 2
self.assertRaises(checker.ValidationError, checker.check_attribute, attr)
def make_attribute(
key: Text,
value: Any,
doc_string: Optional[Text] = None
) -> AttributeProto:
"""Makes an AttributeProto based on the value type."""
attr = AttributeProto()
attr.name = key
if doc_string:
attr.doc_string = doc_string
is_iterable = isinstance(value, collections.abc.Iterable)
bytes_or_false = _to_bytes_or_false(value)
# First, singular cases
# float
if isinstance(value, float):
attr.f = value
attr.type = AttributeProto.FLOAT
# integer
elif isinstance(value, numbers.Integral):
attr.i = cast(int, value)
attr.type = AttributeProto.INT
# string
elif bytes_or_false is not False:
assert isinstance(bytes_or_false, bytes)
attr.s = bytes_or_false
attr.type = AttributeProto.STRING
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
attr.type = AttributeProto.TENSOR
elif isinstance(value, SparseTensorProto):
attr.sparse_tensor.CopyFrom(value)
attr.type = AttributeProto.SPARSE_TENSOR
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
attr.type = AttributeProto.GRAPH
elif isinstance(value, TypeProto):
attr.tp.CopyFrom(value)
attr.type = AttributeProto.TYPE_PROTO
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(isinstance(v, numbers.Real) for v in value):
# Since ints and floats are members of Real, this allows a mix of ints and floats
# (and converts the ints to floats).
attr.floats.extend(float(v) for v in value)
attr.type = AttributeProto.FLOATS
elif all(map(lambda bytes_or_false: bytes_or_false is not False, byte_array)):
attr.strings.extend(cast(List[bytes], byte_array))
attr.type = AttributeProto.STRINGS
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
attr.type = AttributeProto.TENSORS
elif all(isinstance(v, SparseTensorProto) for v in value):
attr.sparse_tensors.extend(value)
attr.type = AttributeProto.SPARSE_TENSORS
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
attr.type = AttributeProto.GRAPHS
elif all(isinstance(tp, TypeProto) for tp in value):
attr.type_protos.extend(value)
attr.type = AttributeProto.TYPE_PROTOS
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type.")
else:
raise TypeError(
'value "{}" is not valid attribute data type.'.format(value))
return attr
def make_attribute(
key, # type: Text
value, # type: Any
dtype=None, # type: [np.float32, np.float64]
domain='', # type: Text
doc_string=None # type: Optional[Text]
): # type: (...) -> AttributeProto
"""Makes an AttributeProto based on the value type."""
attr = AttributeProto()
attr.name = key
if doc_string:
attr.doc_string = doc_string
is_iterable = isinstance(value, collections.abc.Iterable)
bytes_or_false = _to_bytes_or_false(value)
use_float64 = dtype == np.float64 and domain not in ('', 'ai.onnx.ml')
if isinstance(value, np.float32):
attr.f = value
attr.type = AttributeProto.FLOAT
elif isinstance(value, (float, np.float64)):
if use_float64:
attr.type = AttributeProto.TENSOR
attr.t.CopyFrom(
make_tensor(key, TensorProto.DOUBLE, (1, ), [value]))
else:
attr.f = value
attr.type = AttributeProto.FLOAT
elif isinstance(value, np.int32):
attr.i = value
attr.type = AttributeProto.INT
elif isinstance(value, np.int64):
attr.i = value
attr.type = AttributeProto.INT
elif isinstance(value, numbers.Integral):
attr.i = value
attr.type = AttributeProto.INT
# string
elif bytes_or_false is not False:
assert isinstance(bytes_or_false, bytes)
attr.s = bytes_or_false
attr.type = AttributeProto.STRING
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
attr.type = AttributeProto.TENSOR
elif (SparseTensorProto is not None
and isinstance(value, SparseTensorProto)):
attr.sparse_tensor.CopyFrom(value)
attr.type = AttributeProto.SPARSE_TENSOR
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
attr.type = AttributeProto.GRAPH
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, np.float32) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, np.float64) for v in value):
if use_float64:
attr.type = AttributeProto.TENSOR
attr.t.CopyFrom(
make_tensor(key, TensorProto.DOUBLE, (len(value), ),
value))
else:
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, float) for v in value):
if use_float64:
attr.type = AttributeProto.TENSOR
attr.t.CopyFrom(
make_tensor(key, TensorProto.DOUBLE, (len(value), ),
value))
else:
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, np.int32) for v in value):
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(isinstance(v, np.int64) for v in value):
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(
map(lambda bytes_or_false: bytes_or_false is not False,
byte_array)):
attr.strings.extend(cast(List[bytes], byte_array))
attr.type = AttributeProto.STRINGS
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
attr.type = AttributeProto.TENSORS
elif (SparseTensorProto is not None
and all(isinstance(v, SparseTensorProto) for v in value)):
attr.sparse_tensors.extend(value)
attr.type = AttributeProto.SPARSE_TENSORS
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
attr.type = AttributeProto.GRAPHS
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type, key='{}', type={}, dtype={}, "
"types={}.".format(
key, type(value), dtype,
[type(_) for _, __ in zip(value, range(0, 5))]))
else:
raise ValueError(
"Value '{}' is not valid attribute data type for attribute "
"'{}'.".format(value, key))
return attr
def make_attribute(
key, # type: Text
value, # type: Any
doc_string=None # type: Optional[Text]
): # type: (...) -> AttributeProto
"""Makes an AttributeProto based on the value type."""
def getshape(obj):
if hasattr(obj, 'shape'):
return obj.shape
else:
return (len(obj), )
attr = AttributeProto()
attr.name = key
if doc_string:
attr.doc_string = doc_string
is_iterable = isinstance(value, collections.Iterable)
bytes_or_false = _to_bytes_or_false(value)
if isinstance(value, np.float32):
attr.f = value
attr.type = AttributeProto.FLOAT
elif isinstance(value, np.float64):
attr.f = value
attr.type = AttributeProto.FLOAT
elif isinstance(value, float):
attr.f = value
attr.type = AttributeProto.FLOAT
# raise RuntimeError("float is not allowed anymore
# due to ambiguities, "
# "use numpy types, key='{}'.".format(key))
elif isinstance(value, np.int32):
attr.i = value
attr.type = AttributeProto.INT
elif isinstance(value, np.int64):
attr.i = value
attr.type = AttributeProto.INT64
elif isinstance(value, numbers.Integral):
attr.i = value
attr.type = AttributeProto.INT
elif bytes_or_false:
assert isinstance(bytes_or_false, bytes)
attr.s = bytes_or_false
attr.type = AttributeProto.STRING
elif isinstance(value, TensorProto):
attr.t.CopyFrom(value)
attr.type = AttributeProto.TENSOR
elif isinstance(value, GraphProto):
attr.g.CopyFrom(value)
attr.type = AttributeProto.GRAPH
# third, iterable cases
elif is_iterable:
byte_array = [_to_bytes_or_false(v) for v in value]
if all(isinstance(v, np.float32) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
# return make_attribute(
# key, doc_string=doc_string,
# value=make_tensor(
# key, TensorProto.FLOAT,
# getshape(value), value))
elif all(isinstance(v, np.float64) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
# return make_attribute(
# key, doc_string=doc_string,
# value=make_tensor(
# key, TensorProto.DOUBLE,
# getshape(value), value))
elif all(isinstance(v, float) for v in value):
attr.floats.extend(value)
attr.type = AttributeProto.FLOATS
elif all(isinstance(v, np.int32) for v in value):
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
# return make_attribute(
# key, doc_string=doc_string,
# value=make_tensor(
# key, TensorProto.INT32,
# getshape(value), value))
elif all(isinstance(v, np.int64) for v in value):
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
# return make_attribute(
# key, doc_string=doc_string,
# value=make_tensor(
# key, TensorProto.INT64,
# getshape(value), value))
elif all(isinstance(v, numbers.Integral) for v in value):
# Turn np.int32/64 into Python built-in int.
attr.ints.extend(int(v) for v in value)
attr.type = AttributeProto.INTS
elif all(byte_array):
attr.strings.extend(cast(List[bytes], byte_array))
attr.type = AttributeProto.STRINGS
elif all(isinstance(v, TensorProto) for v in value):
attr.tensors.extend(value)
attr.type = AttributeProto.TENSORS
elif all(isinstance(v, GraphProto) for v in value):
attr.graphs.extend(value)
attr.type = AttributeProto.GRAPHS
else:
raise ValueError(
"You passed in an iterable attribute but I cannot figure out "
"its applicable type, key='{}', type={}, types={}.".format(
key, type(value),
[type(_) for _, __ in zip(value, range(0, 5))]))
else:
raise ValueError(
'Value "{}" is not valid attribute data type.'.format(value))
return attr
