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40,537 | pyglove.core.geno.base | __len__ | Returns the number of decision points. | @abc.abstractmethod
def __len__(self) -> int:
"""Returns the number of decision points."""
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|
40,546 | pyglove.core.geno.base | _next_dna | Next DNA generation logic that should be overridden by subclasses. | @abc.abstractmethod
def _next_dna(self, dna: Optional['DNA'] = None) -> Optional['DNA']:
"""Next DNA generation logic that should be overridden by subclasses."""
| (self, dna: Optional[pyglove.core.geno.base.DNA] = None) -> Optional[pyglove.core.geno.base.DNA] | [
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|
40,548 | pyglove.core.geno.base | _on_bound | Event that is triggered when object is modified. | def _on_bound(self):
"""Event that is triggered when object is modified."""
super()._on_bound()
self._id = None
self._named_decision_points_cache = None
self._decision_point_by_id_cache = None
self._userdata = AttributeDict()
| (self) | [
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|
40,552 | pyglove.core.geno.base | _on_path_change | Event that is triggered when path changes. | def _on_path_change(self, old_path, new_path):
"""Event that is triggered when path changes."""
super()._on_path_change(old_path, new_path)
# We invalidate the ID cache and decision_point_by_id cache
# when the ancestor hierarchy changes, which will force the ID and
# the cache to be recomputed upon usage.
self._id = None
self._decision_point_by_id_cache = None
| (self, old_path, new_path) | [
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|
40,553 | pyglove.core.geno.base | _random_dna | Random DNA generation logic that should be overridden by subclasses. | @abc.abstractmethod
def _random_dna(self,
random_generator: Union[types.ModuleType, random.Random],
previous_dna: Optional['DNA']) -> 'DNA':
"""Random DNA generation logic that should be overridden by subclasses."""
| (self, random_generator: Union[module, random.Random], previous_dna: Optional[pyglove.core.geno.base.DNA]) -> pyglove.core.geno.base.DNA | [
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|
40,567 | pyglove.core.geno.base | first_dna | Returns the first DNA in the spec. | def first_dna(self, attach_spec: bool = True) -> 'DNA':
"""Returns the first DNA in the spec."""
return self.next_dna(None, attach_spec)
| (self, attach_spec: bool = True) -> pyglove.core.geno.base.DNA | [
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|
40,569 | pyglove.core.geno.base | get | Get decision point(s) by name or ID. | def get(self,
name_or_id: Union[object_utils.KeyPath, str],
default: Any = None
) -> Union['DecisionPoint', List['DecisionPoint']]:
"""Get decision point(s) by name or ID."""
try:
return self[name_or_id]
except KeyError:
return default
| (self, name_or_id: Union[pyglove.core.object_utils.value_location.KeyPath, str], default: Optional[Any] = None) -> Union[pyglove.core.geno.base.DecisionPoint, List[pyglove.core.geno.base.DecisionPoint]] | [
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|
40,571 | pyglove.core.geno.base | iter_dna | Iterate the DNA in the space represented by this spec.
Args:
dna: An optional DNA as the start point (exclusive) for iteration.
attach_spec: If True, the DNASpec will be attached to the DNA returned.
Yields:
The next DNA according to the spec.
| def iter_dna(self, dna: Optional['DNA'] = None, attach_spec: bool = True):
"""Iterate the DNA in the space represented by this spec.
Args:
dna: An optional DNA as the start point (exclusive) for iteration.
attach_spec: If True, the DNASpec will be attached to the DNA returned.
Yields:
The next DNA according to the spec.
"""
while True:
dna = self.next_dna(dna, attach_spec)
if dna is None:
break
yield dna
| (self, dna: Optional[pyglove.core.geno.base.DNA] = None, attach_spec: bool = True) | [
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|
40,573 | pyglove.core.geno.base | next_dna | Returns the next DNA in the space represented by this spec.
Args:
dna: The DNA whose next will be returned. If None, `next_dna` will return
the first DNA.
attach_spec: If True, current spec will be attached to the returned DNA.
Returns:
The next DNA or None if there is no next DNA.
| def next_dna(self,
dna: Optional['DNA'] = None,
attach_spec: bool = True) -> Optional['DNA']:
"""Returns the next DNA in the space represented by this spec.
Args:
dna: The DNA whose next will be returned. If None, `next_dna` will return
the first DNA.
attach_spec: If True, current spec will be attached to the returned DNA.
Returns:
The next DNA or None if there is no next DNA.
"""
dna = self._next_dna(dna)
if attach_spec and dna is not None:
dna.use_spec(self)
return dna
| (self, dna: Optional[pyglove.core.geno.base.DNA] = None, attach_spec: bool = True) -> Optional[pyglove.core.geno.base.DNA] | [
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|
40,575 | pyglove.core.geno.base | random_dna | Returns a random DNA based on current spec.
Args:
random_generator: An optional Random object. If None, the global random
module will be used.
attach_spec: If True, current spec will be attached to the returned DNA.
previous_dna: An optional DNA representing previous DNA. This field might
be useful for generating stateful random DNAs.
Returns:
A random DNA based on current spec.
| def random_dna(self,
random_generator: Union[types.ModuleType,
random.Random,
None] = None,
attach_spec: bool = True,
previous_dna: Optional['DNA'] = None) -> 'DNA':
"""Returns a random DNA based on current spec.
Args:
random_generator: An optional Random object. If None, the global random
module will be used.
attach_spec: If True, current spec will be attached to the returned DNA.
previous_dna: An optional DNA representing previous DNA. This field might
be useful for generating stateful random DNAs.
Returns:
A random DNA based on current spec.
"""
random_generator = random_generator or random
dna = self._random_dna(random_generator, previous_dna)
if attach_spec:
dna.use_spec(self)
return dna
| (self, random_generator: Union[module, random.Random, NoneType] = None, attach_spec: bool = True, previous_dna: Optional[pyglove.core.geno.base.DNA] = None) -> pyglove.core.geno.base.DNA | [
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|
40,580 | pyglove.core.geno.base | set_userdata | Sets user data.
User data can be used for storing state associated with the DNASpec, and
is not persisted across processes or during serialization. Use `hints` to
carry persistent objects for the DNASpec.
Args:
key: Key of the user data.
value: Value of the user data.
| def set_userdata(self, key: str, value: Any) -> None:
"""Sets user data.
User data can be used for storing state associated with the DNASpec, and
is not persisted across processes or during serialization. Use `hints` to
carry persistent objects for the DNASpec.
Args:
key: Key of the user data.
value: Value of the user data.
"""
self._userdata[key] = value
| (self, key: str, value: Any) -> NoneType | [
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|
40,610 | pyglove.core.geno.base | validate | Validate whether a DNA value conforms to this spec. | @abc.abstractmethod
def validate(self, dna: 'DNA') -> bool:
"""Validate whether a DNA value conforms to this spec."""
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|
40,611 | pyglove.core.symbolic.dict | Dict | Symbolic dict.
``pg.Dict`` implements a dict type whose instances are symbolically
programmable, which is a subclass of the built-in Python ``dict`` and
a subclass of :class:`pyglove.Symbolic`.
``pg.Dict`` provides the following features:
* It a symbolic programmable dict with string keys.
* It enables attribute access on dict keys.
* It supports symbolic validation and value completitions based on schema.
* It provides events to handle sub-nodes changes.
``pg.Dict`` can be used as a regular dict with string keys::
# Construct a symbolic dict from key value pairs.
d = pg.Dict(x=1, y=2)
or::
# Construct a symbolic dict from a mapping object.
d = pg.Dict({'x': 1, 'y': 2})
Besides regular items access using ``[]``, it allows attribute access
to its keys::
# Read access to key `x`.
assert d.x == 1
# Write access to key 'y'.
d.y = 1
``pg.Dict`` supports symbolic validation when the ``value_spec`` argument
is provided::
d = pg.Dict(x=1, y=2, value_spec=pg.typing.Dict([
('x', pg.typing.Int(min_value=1)),
('y', pg.typing.Int(min_value=1)),
(pg.typing.StrKey('foo.*'), pg.typing.Str())
])
# Okay: all keys started with 'foo' is acceptable and are strings.
d.foo1 = 'abc'
# Raises: 'bar' is not acceptable as keys in the dict.
d.bar = 'abc'
Users can mutate the values contained in it::
d = pg.Dict(x=pg.Dict(y=1), p=pg.List([0]))
d.rebind({
'x.y': 2,
'p[0]': 1
})
It also allows the users to subscribe subtree updates::
def on_change(updates):
print(updates)
d = pg.Dict(x=1, onchange_callaback=on_change)
# `on_change` will be triggered on item insertion.
d['y'] = {'z': 1}
# `on_change` will be triggered on item removal.
del d.x
# `on_change` will also be triggered on subtree change.
d.rebind({'y.z': 2})
| class Dict(dict, base.Symbolic, pg_typing.CustomTyping):
"""Symbolic dict.
``pg.Dict`` implements a dict type whose instances are symbolically
programmable, which is a subclass of the built-in Python ``dict`` and
a subclass of :class:`pyglove.Symbolic`.
``pg.Dict`` provides the following features:
* It a symbolic programmable dict with string keys.
* It enables attribute access on dict keys.
* It supports symbolic validation and value completitions based on schema.
* It provides events to handle sub-nodes changes.
``pg.Dict`` can be used as a regular dict with string keys::
# Construct a symbolic dict from key value pairs.
d = pg.Dict(x=1, y=2)
or::
# Construct a symbolic dict from a mapping object.
d = pg.Dict({'x': 1, 'y': 2})
Besides regular items access using ``[]``, it allows attribute access
to its keys::
# Read access to key `x`.
assert d.x == 1
# Write access to key 'y'.
d.y = 1
``pg.Dict`` supports symbolic validation when the ``value_spec`` argument
is provided::
d = pg.Dict(x=1, y=2, value_spec=pg.typing.Dict([
('x', pg.typing.Int(min_value=1)),
('y', pg.typing.Int(min_value=1)),
(pg.typing.StrKey('foo.*'), pg.typing.Str())
])
# Okay: all keys started with 'foo' is acceptable and are strings.
d.foo1 = 'abc'
# Raises: 'bar' is not acceptable as keys in the dict.
d.bar = 'abc'
Users can mutate the values contained in it::
d = pg.Dict(x=pg.Dict(y=1), p=pg.List([0]))
d.rebind({
'x.y': 2,
'p[0]': 1
})
It also allows the users to subscribe subtree updates::
def on_change(updates):
print(updates)
d = pg.Dict(x=1, onchange_callaback=on_change)
# `on_change` will be triggered on item insertion.
d['y'] = {'z': 1}
# `on_change` will be triggered on item removal.
del d.x
# `on_change` will also be triggered on subtree change.
d.rebind({'y.z': 2})
"""
@classmethod
def partial(cls,
dict_obj: Optional[typing.Dict[str, Any]] = None,
value_spec: Optional[pg_typing.Dict] = None,
*,
onchange_callback: Optional[Callable[
[typing.Dict[object_utils.KeyPath, base.FieldUpdate]], None]
] = None, # pylint: disable=bad-continuation
**kwargs) -> 'Dict':
"""Class method that creates a partial Dict object."""
return cls(dict_obj,
value_spec=value_spec,
onchange_callback=onchange_callback,
allow_partial=True,
**kwargs)
@classmethod
def from_json(cls,
json_value: Any,
*,
value_spec: Optional[pg_typing.Dict] = None,
allow_partial: bool = False,
root_path: Optional[object_utils.KeyPath] = None,
**kwargs) -> 'Dict':
"""Class method that load an symbolic Dict from a JSON value.
Args:
json_value: Input JSON value, only JSON dict is acceptable.
value_spec: An optional value spec to apply.
allow_partial: Whether to allow members of the dict to be partial.
root_path: KeyPath of loaded object in its object tree.
**kwargs: Allow passing through keyword arguments that are not applicable.
Returns:
A schemaless symbolic dict. For example::
d = Dict.from_json({
'a': {
'_type': '__main__.Foo',
'f1': 1,
'f2': {
'f21': True
}
}
})
assert d.value_spec is None
# Okay:
d.b = 1
# a.f2 is bound by class Foo's field 'f2' definition (assume it defines
# a schema for the Dict field).
assert d.a.f2.value_spec is not None
# Not okay:
d.a.f2.abc = 1
"""
return cls(json_value,
value_spec=value_spec,
allow_partial=allow_partial,
root_path=root_path)
def __init__(self,
dict_obj: Union[
None,
Iterable[Tuple[str, Any]],
typing.Dict[str, Any]] = None,
*,
value_spec: Optional[pg_typing.Dict] = None,
onchange_callback: Optional[Callable[
[typing.Dict[object_utils.KeyPath, base.FieldUpdate]], None]
] = None, # pylint: disable=bad-continuation
**kwargs):
"""Constructor.
Args:
dict_obj: A dict as initial value for this Dict.
value_spec: Value spec that applies to this Dict.
onchange_callback: Callback when sub-tree has been modified.
**kwargs: Key value pairs that will be inserted into the dict as initial
value, which provides a syntax sugar for usage as below: d =
pg.Dict(a=1, b=2)
"""
if value_spec and not isinstance(value_spec, pg_typing.Dict):
raise TypeError(
f'Argument \'value_spec\' must be a `pg.typing.Dict` object. '
f'Encountered {value_spec}')
allow_partial = kwargs.pop('allow_partial', False)
accessor_writable = kwargs.pop('accessor_writable', True)
sealed = kwargs.pop('sealed', False)
root_path = kwargs.pop('root_path', None)
# Skip schema check when dict_obj is validated against
# schema externally. This flag is helpful to avoid duplicated schema
# check in nested structures, which takes effect only when value_spec
# is not None.
pass_through = kwargs.pop('pass_through', False)
# If True, the parent of dict items should be set to `self.sym_parent`,
# This is useful when Dict is used as the field container of
# pg.Object.
self._set_raw_attr(
'_as_object_attributes_container',
kwargs.pop('as_object_attributes_container', False),
)
# We copy the symbolic form of dict values instead of their evaluated
# values.
if isinstance(dict_obj, Dict):
dict_obj = {k: v for k, v in dict_obj.sym_items()}
elif dict_obj is not None:
dict_obj = dict(dict_obj)
# NOTE(daiyip): we call __init__ of superclasses explicitly instead of
# calling super().__init__(...) since dict.__init__ does
# not follow super(...).__init__ fashion, which will lead to
# Symbolic.__init__ uncalled.
base.Symbolic.__init__(
self,
allow_partial=allow_partial,
accessor_writable=True,
# We delay seal operation until members are filled.
sealed=False,
root_path=root_path)
dict.__init__(self)
self._value_spec = None
self._onchange_callback = None
# NOTE(daiyip): values in kwargs is prior to dict_obj.
dict_obj = dict_obj or {}
for k, v in kwargs.items():
dict_obj[k] = v
if value_spec:
if pass_through:
for k, v in dict_obj.items():
super().__setitem__(k, self._relocate_if_symbolic(k, v))
# NOTE(daiyip): when pass_through is on, we simply trust input
# dict is validated and filled with values of their final form (
# symbolic Dict/List vs. dict/list). This prevents members from
# repeated validation and transformation.
self._value_spec = value_spec
else:
for k, v in dict_obj.items():
super().__setitem__(k, self._formalized_value(k, None, v))
self.use_value_spec(value_spec, allow_partial)
else:
for k, v in dict_obj.items():
self._set_item_without_permission_check(k, v)
# NOTE(daiyip): We set onchange callback at the end of init to avoid
# triggering during initialization.
self._onchange_callback = onchange_callback
self.set_accessor_writable(accessor_writable)
self.seal(sealed)
@property
def value_spec(self) -> Optional[pg_typing.Dict]:
"""Returns value spec of this dict.
NOTE(daiyip): If this dict is schema-less, value_spec will be None.
"""
return self._value_spec
def use_value_spec(self,
value_spec: Optional[pg_typing.Dict],
allow_partial: bool = False) -> 'Dict':
"""Applies a ``pg.typing.Dict`` as the value spec for current dict.
Args: | (dict_obj: Union[NoneType, Iterable[Tuple[str, Any]], Dict[str, Any]] = None, *, value_spec: Optional[pyglove.core.typing.value_specs.Dict] = None, onchange_callback: Optional[Callable[[Dict[pyglove.core.object_utils.value_location.KeyPath, pyglove.core.symbolic.base.FieldUpdate]], NoneType]] = None, **kwargs) | [
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|
40,615 | pyglove.core.symbolic.dict | __delattr__ | Delete an attribute. | def __delattr__(self, name: str) -> None:
"""Delete an attribute."""
del self[name]
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|
40,616 | pyglove.core.symbolic.dict | __delitem__ | Delete a key from the Dict.
This is used to delete a key which resolves to a pg.typing.NonConstKey.
Args:
name: Key to delete.
Raises:
WritePermissionError: When Dict is sealed.
KeyError: When key is not a NonConstKey.
| def __delitem__(self, name: str) -> None:
"""Delete a key from the Dict.
This is used to delete a key which resolves to a pg.typing.NonConstKey.
Args:
name: Key to delete.
Raises:
WritePermissionError: When Dict is sealed.
KeyError: When key is not a NonConstKey.
"""
if base.treats_as_sealed(self):
raise base.WritePermissionError('Cannot del item from a sealed Dict.')
if not base.writtable_via_accessors(self):
raise base.WritePermissionError(
self._error_message('Cannot del Dict field by attribute or key while '
'accessor_writable is set to False. '
'Use \'rebind\' method instead.'))
if name not in self:
raise KeyError(
self._error_message(f'Key does not exist in Dict: {name!r}.'))
update = self._set_item_without_permission_check(
name, pg_typing.MISSING_VALUE)
if flags.is_change_notification_enabled() and update:
self._notify_field_updates([update])
| (self, name: str) -> NoneType | [
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|
40,617 | pyglove.core.symbolic.dict | __eq__ | Operator ==. | def __eq__(self, other: Any) -> bool:
"""Operator ==."""
if isinstance(other, dict):
return dict.__eq__(self, other)
return False
| (self, other: Any) -> bool | [
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|
40,618 | pyglove.core.symbolic.dict | __getattr__ | Get attribute that is not defined as property. | def __getattr__(self, name: str) -> Any:
"""Get attribute that is not defined as property."""
if name in self:
return self.sym_inferred(name)
raise AttributeError(
f'Attribute \'{name}\' does not exist in {self.__class__!r}.')
| (self, name: str) -> Any | [
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|
40,619 | pyglove.core.symbolic.dict | __getitem__ | Get item in this Dict. | def __getitem__(self, key: str) -> Any:
"""Get item in this Dict."""
try:
return self.sym_inferred(key)
except AttributeError as e:
raise KeyError(key) from e
| (self, key: str) -> Any | [
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|
40,620 | pyglove.core.symbolic.dict | __getstate__ | Customizes pickle.dump. | def __getstate__(self) -> Any:
"""Customizes pickle.dump."""
return dict(value=dict(self), kwargs=self._init_kwargs())
| (self) -> Any | [
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|
40,621 | pyglove.core.symbolic.dict | __hash__ | Overridden hashing function using symbolic hash. | def __hash__(self) -> int:
"""Overridden hashing function using symbolic hash."""
return self.sym_hash()
| (self) -> int | [
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|
40,622 | pyglove.core.symbolic.dict | __init__ | Constructor.
Args:
dict_obj: A dict as initial value for this Dict.
value_spec: Value spec that applies to this Dict.
onchange_callback: Callback when sub-tree has been modified.
**kwargs: Key value pairs that will be inserted into the dict as initial
value, which provides a syntax sugar for usage as below: d =
pg.Dict(a=1, b=2)
| def __init__(self,
dict_obj: Union[
None,
Iterable[Tuple[str, Any]],
typing.Dict[str, Any]] = None,
*,
value_spec: Optional[pg_typing.Dict] = None,
onchange_callback: Optional[Callable[
[typing.Dict[object_utils.KeyPath, base.FieldUpdate]], None]
] = None, # pylint: disable=bad-continuation
**kwargs):
"""Constructor.
Args:
dict_obj: A dict as initial value for this Dict.
value_spec: Value spec that applies to this Dict.
onchange_callback: Callback when sub-tree has been modified.
**kwargs: Key value pairs that will be inserted into the dict as initial
value, which provides a syntax sugar for usage as below: d =
pg.Dict(a=1, b=2)
"""
if value_spec and not isinstance(value_spec, pg_typing.Dict):
raise TypeError(
f'Argument \'value_spec\' must be a `pg.typing.Dict` object. '
f'Encountered {value_spec}')
allow_partial = kwargs.pop('allow_partial', False)
accessor_writable = kwargs.pop('accessor_writable', True)
sealed = kwargs.pop('sealed', False)
root_path = kwargs.pop('root_path', None)
# Skip schema check when dict_obj is validated against
# schema externally. This flag is helpful to avoid duplicated schema
# check in nested structures, which takes effect only when value_spec
# is not None.
pass_through = kwargs.pop('pass_through', False)
# If True, the parent of dict items should be set to `self.sym_parent`,
# This is useful when Dict is used as the field container of
# pg.Object.
self._set_raw_attr(
'_as_object_attributes_container',
kwargs.pop('as_object_attributes_container', False),
)
# We copy the symbolic form of dict values instead of their evaluated
# values.
if isinstance(dict_obj, Dict):
dict_obj = {k: v for k, v in dict_obj.sym_items()}
elif dict_obj is not None:
dict_obj = dict(dict_obj)
# NOTE(daiyip): we call __init__ of superclasses explicitly instead of
# calling super().__init__(...) since dict.__init__ does
# not follow super(...).__init__ fashion, which will lead to
# Symbolic.__init__ uncalled.
base.Symbolic.__init__(
self,
allow_partial=allow_partial,
accessor_writable=True,
# We delay seal operation until members are filled.
sealed=False,
root_path=root_path)
dict.__init__(self)
self._value_spec = None
self._onchange_callback = None
# NOTE(daiyip): values in kwargs is prior to dict_obj.
dict_obj = dict_obj or {}
for k, v in kwargs.items():
dict_obj[k] = v
if value_spec:
if pass_through:
for k, v in dict_obj.items():
super().__setitem__(k, self._relocate_if_symbolic(k, v))
# NOTE(daiyip): when pass_through is on, we simply trust input
# dict is validated and filled with values of their final form (
# symbolic Dict/List vs. dict/list). This prevents members from
# repeated validation and transformation.
self._value_spec = value_spec
else:
for k, v in dict_obj.items():
super().__setitem__(k, self._formalized_value(k, None, v))
self.use_value_spec(value_spec, allow_partial)
else:
for k, v in dict_obj.items():
self._set_item_without_permission_check(k, v)
# NOTE(daiyip): We set onchange callback at the end of init to avoid
# triggering during initialization.
self._onchange_callback = onchange_callback
self.set_accessor_writable(accessor_writable)
self.seal(sealed)
| (self, dict_obj: Union[NoneType, Iterable[Tuple[str, Any]], Dict[str, Any]] = None, *, value_spec: Optional[pyglove.core.typing.value_specs.Dict] = None, onchange_callback: Optional[Callable[[Dict[pyglove.core.object_utils.value_location.KeyPath, pyglove.core.symbolic.base.FieldUpdate]], NoneType]] = None, **kwargs) | [
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|
40,623 | pyglove.core.symbolic.dict | __iter__ | Iterate keys in field declaration order. | def __iter__(self):
"""Iterate keys in field declaration order."""
return self.sym_keys()
| (self) | [
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|
40,624 | pyglove.core.symbolic.dict | __ne__ | Operator !=. | def __ne__(self, other: Any) -> bool:
"""Operator !=."""
return not self.__eq__(other)
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|
40,625 | pyglove.core.symbolic.dict | __repr__ | Operator repr(). | def __repr__(self) -> str:
"""Operator repr()."""
return base.Symbolic.__repr__(self)
| (self) -> str | [
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|
40,626 | pyglove.core.symbolic.dict | __setattr__ | Set attribute of this Dict.
NOTE(daiyip): When setting attributes, public attributes (not started with
'_') are set as dict fields, while private attributes (started with '_') are
set on the object instance.
Args:
name: Name of attribute.
value: Value of attribute.
| def __setattr__(self, name: str, value: Any) -> None:
"""Set attribute of this Dict.
NOTE(daiyip): When setting attributes, public attributes (not started with
'_') are set as dict fields, while private attributes (started with '_') are
set on the object instance.
Args:
name: Name of attribute.
value: Value of attribute.
"""
if name.startswith('_'):
super().__setattr__(name, value)
else:
self[name] = value
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|
40,627 | pyglove.core.symbolic.dict | __setitem__ | Set item in this Dict.
Args:
key: String key. (Please be noted that key path is not supported.)
value: Value to be inserted.
Raises:
WritePermissionError: when Dict cannot be modified by accessor or
is sealed.
KeyError: Key is not allowed according to the value spec.
ValueError: Value is not acceptable according to the value spec.
| def __setitem__(self, key: str, value: Any) -> None:
"""Set item in this Dict.
Args:
key: String key. (Please be noted that key path is not supported.)
value: Value to be inserted.
Raises:
WritePermissionError: when Dict cannot be modified by accessor or
is sealed.
KeyError: Key is not allowed according to the value spec.
ValueError: Value is not acceptable according to the value spec.
"""
# NOTE(daiyip): THIS IS A WORKAROUND FOR WORKING WITH PICKLE.
# `pg.Dict` is a subclass of `dict`, therefore, when pickle loads a dict,
# it will try to set its items directly by calling `__setitem__` without
# calling `pg.Dict.__init__` at the first place. As a result, an error will
# raise, which complains about that an attribute set up during `__init__` is
# not available. A mitigation to this issue is to detect such calls in
# `__setitem__` as the follows, and simply do nothing, which will give a
# chance to `pg.Dict.__getstate__` to deal with the restoration logic as
# an object (instead of a dict).
if not hasattr(self, '_sym_parent'):
return
if base.treats_as_sealed(self):
raise base.WritePermissionError(
self._error_message('Cannot modify field of a sealed Dict.'))
if not base.writtable_via_accessors(self):
raise base.WritePermissionError(
self._error_message(
'Cannot modify Dict field by attribute or key while '
'accessor_writable is set to False. '
'Use \'rebind\' method instead.'))
update = self._set_item_without_permission_check(key, value)
if flags.is_change_notification_enabled() and update:
self._notify_field_updates([update])
| (self, key: str, value: Any) -> NoneType | [
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|
40,628 | pyglove.core.symbolic.dict | __setstate__ | Customizes pickle.load. | def __setstate__(self, state) -> None:
"""Customizes pickle.load."""
self.__init__(state['value'], **state['kwargs'])
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|
40,630 | pyglove.core.symbolic.dict | _diff_base | Computes the diff between a value and a base value. | def _diff_base(self, value: Any, base_value: Any) -> Any:
"""Computes the diff between a value and a base value."""
if base.eq(value, base_value):
return pg_typing.MISSING_VALUE
if (isinstance(value, list)
or not isinstance(value, base.Symbolic)
or pg_typing.MISSING_VALUE == base_value):
return value
if value.__class__ is base_value.__class__:
getter = lambda x, k: x.sym_getattr(k)
elif isinstance(value, dict) and isinstance(base_value, dict):
getter = lambda x, k: x[k]
else:
return value
diff = {}
for k, v in value.sym_items():
base_v = getter(base_value, k)
child_diff = self._diff_base(v, base_v)
if pg_typing.MISSING_VALUE != child_diff:
diff[k] = child_diff
return diff
| (self, value: Any, base_value: Any) -> Any | [
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|
40,632 | pyglove.core.symbolic.dict | _formalized_value | Get transformed (formal) value from user input. | def _formalized_value(self, name: str,
field: Optional[pg_typing.Field],
value: Any) -> Any:
"""Get transformed (formal) value from user input."""
allow_partial = base.accepts_partial(self)
if field and pg_typing.MISSING_VALUE == value:
# NOTE(daiyip): default value is already in transformed form.
value = field.default_value
else:
value = base.from_json(
value,
allow_partial=allow_partial,
root_path=object_utils.KeyPath(name, self.sym_path))
if field and flags.is_type_check_enabled():
value = field.apply(
value,
allow_partial=allow_partial,
transform_fn=base.symbolic_transform_fn(self._allow_partial),
root_path=object_utils.KeyPath(name, self.sym_path))
return self._relocate_if_symbolic(name, value)
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|
40,633 | pyglove.core.symbolic.dict | _init_kwargs | null | def _init_kwargs(self) -> typing.Dict[str, Any]:
kwargs = super()._init_kwargs()
if not self._accessor_writable:
kwargs['accessor_writable'] = False
if self._onchange_callback is not None:
kwargs['onchange_callback'] = self._onchange_callback
# NOTE(daiyip): We do not serialize ValueSpec for now as in most use
# cases they come from the subclasses of `pg.Object`.
return kwargs
| (self) -> Dict[str, Any] | [
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|
40,636 | pyglove.core.symbolic.dict | _on_change | On change event of Dict. | def _on_change(self, field_updates: typing.Dict[object_utils.KeyPath,
base.FieldUpdate]):
"""On change event of Dict."""
if self._onchange_callback:
self._onchange_callback(field_updates)
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|
40,639 | pyglove.core.symbolic.dict | _set_item_without_permission_check | Set item without permission check. | def _set_item_without_permission_check( # pytype: disable=signature-mismatch # overriding-parameter-type-checks
self, key: str, value: Any) -> Optional[base.FieldUpdate]:
"""Set item without permission check."""
if not isinstance(key, str):
raise KeyError(self._error_message(
f'Key must be string type. Encountered {key!r}.'))
old_value = self.get(key, pg_typing.MISSING_VALUE)
if old_value is value:
return None
field = None
if self._value_spec and self._value_spec.schema:
field = self._value_spec.schema.get_field(key)
if not field:
if (self.sym_parent is not None
and self.sym_parent.sym_path == self.sym_path):
container_cls = self.sym_parent.__class__
else:
container_cls = self.__class__
raise KeyError(
self._error_message(
f'Key \'{key}\' is not allowed for {container_cls}.'))
# Detach old value from object tree.
if isinstance(old_value, base.TopologyAware):
old_value.sym_setparent(None)
old_value.sym_setpath(object_utils.KeyPath())
if (pg_typing.MISSING_VALUE == value and
(not field or isinstance(field.key, pg_typing.NonConstKey))):
if key in self:
# Using pg.MISSING_VALUE for deleting keys.
super().__delitem__(key)
new_value = pg_typing.MISSING_VALUE
else:
# This condition could trigger when copying a partial Dict to a Dict
# without schema.
return None
else:
new_value = self._formalized_value(key, field, value)
super().__setitem__(key, new_value)
# NOTE(daiyip): If current dict is the field dict of a symbolic object,
# Use parent object as update target.
target = self
if (self.sym_parent is not None
and self.sym_parent.sym_path == self.sym_path):
target = self.sym_parent
return base.FieldUpdate(
self.sym_path + key, target, field, old_value, new_value)
| (self, key: str, value: Any) -> Optional[pyglove.core.symbolic.base.FieldUpdate] | [
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|
40,641 | pyglove.core.symbolic.dict | _sym_clone | Override Symbolic._sym_clone. | def _sym_clone(self, deep: bool, memo=None) -> 'Dict':
"""Override Symbolic._sym_clone."""
source = dict()
for k, v in self.sym_items():
if deep or isinstance(v, base.Symbolic):
v = base.clone(v, deep, memo)
source[k] = v
return Dict(
source,
value_spec=self._value_spec,
allow_partial=self._allow_partial,
accessor_writable=self._accessor_writable,
sealed=self._sealed,
onchange_callback=self._onchange_callback,
# NOTE(daiyip): parent and root_path are reset to empty
# for copy object.
root_path=None,
pass_through=True)
| (self, deep: bool, memo=None) -> pyglove.core.symbolic.dict.Dict | [
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|
40,642 | pyglove.core.symbolic.dict | _sym_getattr | Gets symbolic attribute by key. | def _sym_getattr( # pytype: disable=signature-mismatch # overriding-parameter-type-checks
self, key: str) -> Any:
"""Gets symbolic attribute by key."""
return super().__getitem__(key)
| (self, key: str) -> Any | [
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|
40,644 | pyglove.core.symbolic.dict | _sym_missing | Returns missing values.
Returns:
A dict of key to MISSING_VALUE.
| def _sym_missing(self) -> typing.Dict[str, Any]:
"""Returns missing values.
Returns:
A dict of key to MISSING_VALUE.
"""
missing = dict()
if self._value_spec and self._value_spec.schema:
matched_keys, _ = self._value_spec.schema.resolve(self.keys())
for key_spec, keys in matched_keys.items():
field = self._value_spec.schema[key_spec]
assert keys or isinstance(key_spec, pg_typing.NonConstKey), key_spec
if keys:
for key in keys:
v = self.sym_getattr(key)
if object_utils.MISSING_VALUE == v:
missing[key] = field.value.default
else:
if isinstance(v, base.Symbolic):
missing_child = v.sym_missing(flatten=False)
if missing_child:
missing[key] = missing_child
else:
for k, v in self.sym_items():
if isinstance(v, base.Symbolic):
missing_child = v.sym_missing(flatten=False)
if missing_child:
missing[k] = missing_child
return missing
| (self) -> Dict[str, Any] | [
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|
40,645 | pyglove.core.symbolic.dict | _sym_nondefault | Returns non-default values as key/value pairs in a dict. | def _sym_nondefault(self) -> typing.Dict[str, Any]:
"""Returns non-default values as key/value pairs in a dict."""
non_defaults = dict()
if self._value_spec is not None and self._value_spec.schema:
dict_schema = self._value_spec.schema
matched_keys, _ = dict_schema.resolve(self.keys())
for key_spec, keys in matched_keys.items():
value_spec = dict_schema[key_spec].value
for key in keys:
diff = self._diff_base(self.sym_getattr(key), value_spec.default)
if pg_typing.MISSING_VALUE != diff:
non_defaults[key] = diff
else:
for k, v in self.sym_items():
if isinstance(v, base.Symbolic):
non_defaults_child = v.sym_nondefault(flatten=False)
if non_defaults_child:
non_defaults[k] = non_defaults_child
else:
non_defaults[k] = v
return non_defaults
| (self) -> Dict[str, Any] | [
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|
40,646 | pyglove.core.symbolic.dict | _sym_parent_for_children | null | def _sym_parent_for_children(self) -> Optional[base.Symbolic]:
if self._as_object_attributes_container:
return self.sym_parent
return self
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|
40,647 | pyglove.core.symbolic.dict | _sym_rebind | Subclass specific rebind implementation. | def _sym_rebind(
self, path_value_pairs: typing.Dict[object_utils.KeyPath, Any]
) -> List[base.FieldUpdate]:
"""Subclass specific rebind implementation."""
updates = []
for k, v in path_value_pairs.items():
update = self._set_item_of_current_tree(k, v)
if update is not None:
updates.append(update)
return updates
| (self, path_value_pairs: Dict[pyglove.core.object_utils.value_location.KeyPath, Any]) -> List[pyglove.core.symbolic.base.FieldUpdate] | [
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|
40,648 | pyglove.core.symbolic.dict | _update_children_paths | Update children paths according to root_path of current node. | def _update_children_paths(
self,
old_path: object_utils.KeyPath,
new_path: object_utils.KeyPath) -> None:
"""Update children paths according to root_path of current node."""
del old_path
for k, v in self.sym_items():
if isinstance(v, base.TopologyAware):
v.sym_setpath(object_utils.KeyPath(k, new_path))
| (self, old_path: pyglove.core.object_utils.value_location.KeyPath, new_path: pyglove.core.object_utils.value_location.KeyPath) -> NoneType | [
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|
40,649 | pyglove.core.symbolic.dict | clear | Removes all the keys in current dict. | def clear(self) -> None:
"""Removes all the keys in current dict."""
if base.treats_as_sealed(self):
raise base.WritePermissionError('Cannot clear a sealed Dict.')
value_spec = self._value_spec
self._value_spec = None
super().clear()
if value_spec:
self.use_value_spec(value_spec, self._allow_partial)
| (self) -> NoneType | [
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|
40,651 | pyglove.core.symbolic.dict | copy | Overridden copy using symbolic copy. | def copy(self) -> 'Dict':
"""Overridden copy using symbolic copy."""
return self.sym_clone(deep=False)
| (self) -> pyglove.core.symbolic.dict.Dict | [
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|
40,652 | pyglove.core.symbolic.dict | custom_apply | Implement pg.typing.CustomTyping interface.
Args:
path: KeyPath of current object.
value_spec: Origin value spec of the field.
allow_partial: Whether allow partial object to be created.
child_transform: Function to transform child node values in dict_obj into
their final values. Transform function is called on leaf nodes first,
then on their containers, recursively.
Returns:
A tuple (proceed_with_standard_apply, transformed value)
| def custom_apply(
self,
path: object_utils.KeyPath,
value_spec: pg_typing.ValueSpec,
allow_partial: bool,
child_transform: Optional[
Callable[[object_utils.KeyPath, pg_typing.Field, Any], Any]] = None
) -> Tuple[bool, 'Dict']:
"""Implement pg.typing.CustomTyping interface.
Args:
path: KeyPath of current object.
value_spec: Origin value spec of the field.
allow_partial: Whether allow partial object to be created.
child_transform: Function to transform child node values in dict_obj into
their final values. Transform function is called on leaf nodes first,
then on their containers, recursively.
Returns:
A tuple (proceed_with_standard_apply, transformed value)
"""
proceed_with_standard_apply = True
if self._value_spec:
if value_spec and not value_spec.is_compatible(self._value_spec):
raise ValueError(
object_utils.message_on_path(
f'Dict (spec={self._value_spec!r}) cannot be assigned to an '
f'incompatible field (spec={value_spec!r}).', path))
if self._allow_partial == allow_partial:
proceed_with_standard_apply = False
else:
self._allow_partial = allow_partial
elif isinstance(value_spec, pg_typing.Dict):
self._value_spec = value_spec
return (proceed_with_standard_apply, self)
| (self, path: pyglove.core.object_utils.value_location.KeyPath, value_spec: pyglove.core.typing.class_schema.ValueSpec, allow_partial: bool, child_transform: Optional[Callable[[pyglove.core.object_utils.value_location.KeyPath, pyglove.core.typing.class_schema.Field, Any], Any]] = None) -> Tuple[bool, pyglove.core.symbolic.dict.Dict] | [
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|
40,653 | pyglove.core.symbolic.dict | format | Formats this Dict. | def format(
self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
*,
python_format: bool = False,
hide_default_values: bool = False,
hide_missing_values: bool = False,
include_keys: Optional[Set[str]] = None,
exclude_keys: Optional[Set[str]] = None,
use_inferred: bool = False,
cls_name: Optional[str] = None,
bracket_type: object_utils.BracketType = object_utils.BracketType.CURLY,
key_as_attribute: bool = False,
extra_blankline_for_field_docstr: bool = False,
**kwargs) -> str:
"""Formats this Dict."""
cls_name = cls_name or ''
exclude_keys = exclude_keys or set()
def _indent(text, indent):
return ' ' * 2 * indent + text
def _should_include_key(key):
if include_keys:
return key in include_keys
return key not in exclude_keys
field_list = []
if self._value_spec and self._value_spec.schema:
matched_keys, unmatched = self._value_spec.schema.resolve(self.keys()) # pytype: disable=attribute-error
assert not unmatched
for key_spec, keys in matched_keys.items():
for key in keys:
if _should_include_key(key):
field = self._value_spec.schema[key_spec]
v = self.sym_getattr(key)
if use_inferred and isinstance(v, base.Inferential):
v = self.sym_inferred(key, default=v)
if pg_typing.MISSING_VALUE == v:
if hide_missing_values:
continue
elif hide_default_values and base.eq(v, field.default_value):
continue
field_list.append((field, key, v))
else:
for k, v in self.sym_items():
if _should_include_key(k):
if use_inferred and isinstance(v, base.Inferential):
v = self.sym_inferred(k, default=v)
field_list.append((None, k, v))
open_bracket, close_bracket = object_utils.bracket_chars(bracket_type)
if not field_list:
return f'{cls_name}{open_bracket}{close_bracket}'
if compact:
s = [f'{cls_name}{open_bracket}']
kv_strs = []
for _, k, v in field_list:
v_str = object_utils.format(
v,
compact,
verbose,
root_indent + 1,
hide_default_values=hide_default_values,
hide_missing_values=hide_missing_values,
python_format=python_format,
use_inferred=use_inferred,
extra_blankline_for_field_docstr=extra_blankline_for_field_docstr,
**kwargs)
if not python_format or key_as_attribute:
kv_strs.append(f'{k}={v_str}')
else:
kv_strs.append(f'\'{k}\': {v_str}')
s.append(', '.join(kv_strs))
s.append(close_bracket)
else:
s = [f'{cls_name}{open_bracket}\n']
for i, (f, k, v) in enumerate(field_list):
if i != 0:
s.append(',\n')
if verbose and f and typing.cast(pg_typing.Field, f).description:
if i != 0 and extra_blankline_for_field_docstr:
s.append('\n')
description = typing.cast(pg_typing.Field, f).description
for line in description.split('\n'):
s.append(_indent(f'# {line}\n', root_indent + 1))
v_str = object_utils.format(
v,
compact,
verbose,
root_indent + 1,
hide_default_values=hide_default_values,
hide_missing_values=hide_missing_values,
python_format=python_format,
use_inferred=use_inferred,
extra_blankline_for_field_docstr=extra_blankline_for_field_docstr,
**kwargs)
if not python_format:
# Format in PyGlove's format (default).
s.append(_indent(f'{k} = {v_str}', root_indent + 1))
elif key_as_attribute:
# Format `pg.Objects` under Python format.
s.append(_indent(f'{k}={v_str}', root_indent + 1))
else:
# Format regular `pg.Dict` under Python format.
s.append(_indent(f'\'{k}\': {v_str}', root_indent + 1))
s.append('\n')
s.append(_indent(close_bracket, root_indent))
return ''.join(s)
| (self, compact: bool = False, verbose: bool = True, root_indent: int = 0, *, python_format: bool = False, hide_default_values: bool = False, hide_missing_values: bool = False, include_keys: Optional[Set[str]] = None, exclude_keys: Optional[Set[str]] = None, use_inferred: bool = False, cls_name: Optional[str] = None, bracket_type: pyglove.core.object_utils.formatting.BracketType = <BracketType.CURLY: 2>, key_as_attribute: bool = False, extra_blankline_for_field_docstr: bool = False, **kwargs) -> str | [
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|
40,655 | pyglove.core.symbolic.dict | items | Returns an iterator of (key, value) items in current dict. | def items(self) -> Iterator[Tuple[str, Any]]: # pytype: disable=signature-mismatch
"""Returns an iterator of (key, value) items in current dict."""
return self.sym_items()
| (self) -> Iterator[Tuple[str, Any]] | [
0.05057375133037567,
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|
40,656 | pyglove.core.symbolic.dict | keys | Returns an iterator of keys in current dict. | def keys(self) -> Iterator[str]: # pytype: disable=signature-mismatch
"""Returns an iterator of keys in current dict."""
return self.sym_keys()
| (self) -> Iterator[str] | [
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|
40,659 | pyglove.core.symbolic.dict | pop | Pops a key from current dict. | def pop(
self, key: Any, default: Any = base.RAISE_IF_NOT_FOUND # pylint: disable=protected-access
) -> Any:
"""Pops a key from current dict."""
if key in self:
value = self[key]
with flags.allow_writable_accessors(True):
del self[key]
return value if value != pg_typing.MISSING_VALUE else default
if default is base.RAISE_IF_NOT_FOUND:
raise KeyError(key)
return default
| (self, key: Any, default: Any = (MISSING_VALUE,)) -> Any | [
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|
40,660 | pyglove.core.symbolic.dict | popitem | null | def popitem(self) -> Tuple[str, Any]:
if self._value_spec is not None:
raise ValueError(
'\'popitem\' cannot be performed on a Dict with value spec.')
if base.treats_as_sealed(self):
raise base.WritePermissionError('Cannot pop item from a sealed Dict.')
return super().popitem()
| (self) -> Tuple[str, Any] | [
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|
40,663 | pyglove.core.symbolic.dict | seal | Seals or unseals current object from further modification. | def seal(self, sealed: bool = True) -> 'Dict':
"""Seals or unseals current object from further modification."""
if self.is_sealed == sealed:
return self
for v in self.sym_values():
if isinstance(v, base.Symbolic):
v.seal(sealed)
super().seal(sealed)
return self
| (self, sealed: bool = True) -> pyglove.core.symbolic.dict.Dict | [
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|
40,665 | pyglove.core.symbolic.dict | setdefault | Sets default as the value to key if not present. | def setdefault(self, key: str, default: Any = None) -> Any:
"""Sets default as the value to key if not present."""
value = pg_typing.MISSING_VALUE
if key in self:
value = self.sym_getattr(key)
if value == pg_typing.MISSING_VALUE:
self[key] = default
value = default
return value
| (self, key: str, default: Optional[Any] = None) -> Any | [
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|
40,667 | pyglove.core.symbolic.dict | sym_attr_field | Returns the field definition for a symbolic attribute. | def sym_attr_field(
self, key: Union[str, int]
) -> Optional[pg_typing.Field]:
"""Returns the field definition for a symbolic attribute."""
if self._value_spec is None or self._value_spec.schema is None:
return None
return self._value_spec.schema.get_field(key) # pytype: disable=attribute-error
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|
40,671 | pyglove.core.symbolic.base | sym_eq | Returns if this object equals to another object symbolically. | def sym_eq(self, other: Any) -> bool:
"""Returns if this object equals to another object symbolically."""
return eq(self, other)
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|
40,676 | pyglove.core.symbolic.dict | sym_hasattr | Tests if a symbolic attribute exists. | def sym_hasattr(self, key: Union[str, int]) -> bool:
"""Tests if a symbolic attribute exists."""
return key in self
| (self, key: Union[str, int]) -> bool | [
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|
40,677 | pyglove.core.symbolic.dict | sym_hash | Symbolic hashing. | def sym_hash(self) -> int:
"""Symbolic hashing."""
return base.sym_hash(
(self.__class__,
tuple([(k, base.sym_hash(v)) for k, v in self.sym_items()
if v != pg_typing.MISSING_VALUE])))
| (self) -> int | [
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|
40,680 | pyglove.core.symbolic.dict | sym_items | Iterates the (key, value) pairs of symbolic attributes. | def sym_items(self) -> Iterator[
Tuple[str, Any]]:
"""Iterates the (key, value) pairs of symbolic attributes."""
for k in self.sym_keys():
yield k, self._sym_getattr(k)
| (self) -> Iterator[Tuple[str, Any]] | [
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|
40,681 | pyglove.core.symbolic.dict | sym_jsonify | Converts current object to a dict with plain Python objects. | def sym_jsonify(
self,
hide_default_values: bool = False,
exclude_keys: Optional[Sequence[str]] = None,
use_inferred: bool = False,
**kwargs) -> object_utils.JSONValueType:
"""Converts current object to a dict with plain Python objects."""
exclude_keys = set(exclude_keys or [])
if self._value_spec and self._value_spec.schema:
json_repr = dict()
matched_keys, _ = self._value_spec.schema.resolve(self.keys()) # pytype: disable=attribute-error
for key_spec, keys in matched_keys.items():
# NOTE(daiyip): The key values of frozen field can safely be excluded
# since they will be the same for a class.
field = self._value_spec.schema[key_spec]
if not field.frozen:
for key in keys:
if key not in exclude_keys:
value = self.sym_getattr(key)
if use_inferred and isinstance(value, base.Inferential):
value = self.sym_inferred(key, default=value)
if pg_typing.MISSING_VALUE == value:
continue
if hide_default_values and base.eq(value, field.default_value):
continue
json_repr[key] = base.to_json(
value, hide_default_values=hide_default_values,
use_inferred=use_inferred,
**kwargs)
return json_repr
else:
return {
k: base.to_json(
self.sym_inferred(k, default=v) if (
use_inferred and isinstance(v, base.Inferential)) else v,
hide_default_values=hide_default_values,
use_inferred=use_inferred,
**kwargs)
for k, v in self.sym_items()
if k not in exclude_keys
}
| (self, hide_default_values: bool = False, exclude_keys: Optional[Sequence[str]] = None, use_inferred: bool = False, **kwargs) -> Union[int, float, bool, str, List[Any], Dict[str, Any]] | [
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|
40,682 | pyglove.core.symbolic.dict | sym_keys | Iterates the keys of symbolic attributes. | def sym_keys(self) -> Iterator[str]:
"""Iterates the keys of symbolic attributes."""
if self._value_spec is None or self._value_spec.schema is None:
for key in super().__iter__():
yield key
else:
traversed = set()
for key_spec in self._value_spec.schema.keys(): # pytype: disable=attribute-error
if isinstance(key_spec, pg_typing.ConstStrKey) and key_spec in self:
yield key_spec.text
traversed.add(key_spec.text)
if len(traversed) < len(self):
for key in super().__iter__():
if key not in traversed:
yield key
| (self) -> Iterator[str] | [
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|
40,683 | pyglove.core.symbolic.base | sym_lt | Returns True if this object is symbolically less than other object. | def sym_lt(self, other: Any) -> bool:
"""Returns True if this object is symbolically less than other object."""
return lt(self, other)
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|
40,690 | pyglove.core.symbolic.dict | sym_setparent | Override set parent of Dict to handle the passing through scenario. | def sym_setparent(self, parent: base.Symbolic):
"""Override set parent of Dict to handle the passing through scenario."""
super().sym_setparent(parent)
# NOTE(daiyip): when flag `as_object_attributes_container` is on, it sets
# the parent of child symbolic values using its parent.
if self._as_object_attributes_container:
for v in self.sym_values():
if isinstance(v, base.TopologyAware):
v.sym_setparent(parent)
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|
40,692 | pyglove.core.symbolic.dict | sym_values | Iterates the values of symbolic attributes. | def sym_values(self) -> Iterator[Any]:
"""Iterates the values of symbolic attributes."""
for k in self.sym_keys():
yield self._sym_getattr(k)
| (self) -> Iterator[Any] | [
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|
40,695 | pyglove.core.symbolic.dict | update | Update Dict with the same semantic as update on standard dict. | def update(self,
other: Union[
None,
typing.Dict[str, Any],
Iterable[Tuple[str, Any]]] = None,
**kwargs) -> None: # pytype: disable=signature-mismatch
"""Update Dict with the same semantic as update on standard dict."""
updates = dict(other) if other else {}
updates.update(kwargs)
self.rebind(
updates, raise_on_no_change=False, skip_notification=True)
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|
40,696 | pyglove.core.symbolic.dict | use_value_spec | Applies a ``pg.typing.Dict`` as the value spec for current dict.
Args:
value_spec: A Dict ValueSpec to apply to this Dict.
If current Dict is schema-less (whose immediate members are not
validated against schema), and `value_spec` is not None, the value spec
will be applied to the Dict.
Or else if current Dict is already symbolic (whose immediate members
are under the constraint of a Dict value spec), and `value_spec` is
None, current Dict will become schema-less. However, the schema
constraints for non-immediate members will remain.
allow_partial: Whether allow partial dict based on the schema. This flag
will override allow_partial flag in __init__ for spec-less Dict.
Returns:
Self.
Raises:
ValueError: validation failed due to value error.
RuntimeError: Dict is already bound with another spec.
TypeError: type errors during validation.
KeyError: key errors during validation.
| def use_value_spec(self,
value_spec: Optional[pg_typing.Dict],
allow_partial: bool = False) -> 'Dict':
"""Applies a ``pg.typing.Dict`` as the value spec for current dict.
Args:
value_spec: A Dict ValueSpec to apply to this Dict.
If current Dict is schema-less (whose immediate members are not
validated against schema), and `value_spec` is not None, the value spec
will be applied to the Dict.
Or else if current Dict is already symbolic (whose immediate members
are under the constraint of a Dict value spec), and `value_spec` is
None, current Dict will become schema-less. However, the schema
constraints for non-immediate members will remain.
allow_partial: Whether allow partial dict based on the schema. This flag
will override allow_partial flag in __init__ for spec-less Dict.
Returns:
Self.
Raises:
ValueError: validation failed due to value error.
RuntimeError: Dict is already bound with another spec.
TypeError: type errors during validation.
KeyError: key errors during validation.
"""
if value_spec is None:
self._value_spec = None
self._accessor_writable = True
return self
if not isinstance(value_spec, pg_typing.Dict):
raise ValueError(
self._error_message(
f'Value spec for list must be a `pg.typing.Dict` object. '
f'Encountered: {value_spec!r}'))
if self._value_spec and self._value_spec != value_spec:
raise RuntimeError(
self._error_message(
f'Dict is already bound with a different value spec: '
f'{self._value_spec}. New value spec: {value_spec}.'))
self._allow_partial = allow_partial
if flags.is_type_check_enabled():
# NOTE(daiyip): self._value_spec will be set in Dict.custom_apply method
# called by value_spec.apply, thus we don't need to set self._value_spec
# explicitly.
value_spec.apply(
self,
allow_partial=base.accepts_partial(self),
child_transform=base.symbolic_transform_fn(self._allow_partial),
root_path=self.sym_path)
else:
self._value_spec = value_spec
return self
| (self, value_spec: Optional[pyglove.core.typing.value_specs.Dict], allow_partial: bool = False) -> pyglove.core.symbolic.dict.Dict | [
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|
40,697 | pyglove.core.symbolic.dict | values | Returns an iterator of values in current dict.. | def values(self) -> Iterator[Any]: # pytype: disable=signature-mismatch
"""Returns an iterator of values in current dict.."""
return self.sym_values()
| (self) -> Iterator[Any] | [
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|
40,698 | pyglove.core.symbolic.diff | Diff | A value diff between two objects: a 'left' object and a 'right' object.
If one of them is missing, it may be represented by pg.Diff.MISSING
For example::
>>> pg.Diff(3.14, 1.618)
Diff(left=3.14, right=1.618)
>>> pg.Diff('hello world', pg.Diff.MISSING)
Diff(left='hello world', right=MISSING)
| class Diff(PureSymbolic, pg_object.Object):
"""A value diff between two objects: a 'left' object and a 'right' object.
If one of them is missing, it may be represented by pg.Diff.MISSING
For example::
>>> pg.Diff(3.14, 1.618)
Diff(left=3.14, right=1.618)
>>> pg.Diff('hello world', pg.Diff.MISSING)
Diff(left='hello world', right=MISSING)
"""
class _Missing:
"""Represents an absent party in a Diff."""
def __repr__(self):
return self.__str__()
def __str__(self):
return 'MISSING'
def __eq__(self, other):
return isinstance(other, Diff._Missing)
def __ne__(self, other):
return not self.__eq__(other)
MISSING = _Missing()
def _on_bound(self):
super()._on_bound()
if self.children:
if not isinstance(self.left, type):
raise ValueError(
f'\'left\' must be a type when \'children\' is specified. '
f'Encountered: {self.left!r}.')
if not isinstance(self.right, type):
raise ValueError(
f'\'right\' must be a type when \'children\' is specified. '
f'Encountered: {self.right!r}.')
self._has_diff = None
@property
def is_leaf(self) -> bool:
"""Returns True if current Diff does not contain inner Diff object."""
return not self.children
def __bool__(self):
"""Returns True if there is a diff."""
if self._has_diff is None:
if base.ne(self.left, self.right):
has_diff = True
elif self.children:
has_diff = any(bool(cd) for cd in self.children.values())
else:
has_diff = False
self._has_diff = has_diff
return self._has_diff
def sym_eq(self, other: Any):
"""Override symbolic equality."""
if super().sym_eq(other):
return True
if not bool(self):
return base.eq(self.left, other)
@property
def value(self):
"""Returns the value if left and right are the same."""
if bool(self):
raise ValueError(
f'\'value\' cannot be accessed when \'left\' and \'right\' '
f'are not the same. Left={self.left!r}, Right={self.right!r}.')
return self.left
def format(
self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
**kwargs):
"""Override format to conditionally print the shared value or the diff."""
if not bool(self):
if self.value == Diff.MISSING:
return 'No diff'
# When there is no diff, but the same value needs to be displayed
# we simply return the value.
return object_utils.format(
self.value, compact, verbose, root_indent, **kwargs)
if self.is_leaf:
exclude_keys = kwargs.pop('exclude_keys', None)
exclude_keys = exclude_keys or set()
exclude_keys.add('children')
return super().format(
compact, verbose, root_indent, exclude_keys=exclude_keys, **kwargs)
else:
assert isinstance(self.left, type)
assert isinstance(self.right, type)
if self.left is self.right and issubclass(self.left, list):
return self.children.format(
compact=compact,
verbose=verbose,
root_indent=root_indent,
cls_name='',
bracket_type=object_utils.BracketType.SQUARE)
if self.left is self.right:
cls_name = self.left.__name__
else:
cls_name = f'{self.left.__name__}|{self.right.__name__}'
return self.children.format(
compact=compact,
verbose=verbose,
root_indent=root_indent,
cls_name=cls_name,
bracket_type=object_utils.BracketType.ROUND)
| (left=MISSING, right=MISSING, children: Dict[str, Any] = {}) | [
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|
40,700 | pyglove.core.symbolic.diff | __bool__ | Returns True if there is a diff. | def __bool__(self):
"""Returns True if there is a diff."""
if self._has_diff is None:
if base.ne(self.left, self.right):
has_diff = True
elif self.children:
has_diff = any(bool(cd) for cd in self.children.values())
else:
has_diff = False
self._has_diff = has_diff
return self._has_diff
| (self) | [
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|
40,717 | pyglove.core.symbolic.diff | _on_bound | null | def _on_bound(self):
super()._on_bound()
if self.children:
if not isinstance(self.left, type):
raise ValueError(
f'\'left\' must be a type when \'children\' is specified. '
f'Encountered: {self.left!r}.')
if not isinstance(self.right, type):
raise ValueError(
f'\'right\' must be a type when \'children\' is specified. '
f'Encountered: {self.right!r}.')
self._has_diff = None
| (self) | [
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|
40,735 | pyglove.core.symbolic.pure_symbolic | custom_apply | Custom apply on a value based on its original value spec.
This implements ``pg.pg_typing.CustomTyping``, allowing a pure symbolic
value to be assigned to any field. To customize this behavior, override
this method in subclasses.
Args:
path: KeyPath of current object under its object tree.
value_spec: Original value spec for this field.
allow_partial: Whether allow partial object to be created.
child_transform: Function to transform child node values into their final
values. Transform function is called on leaf nodes first, then on their
parents, recursively.
Returns:
A tuple (proceed_with_standard_apply, value_to_proceed).
If proceed_with_standard_apply is set to False, value_to_proceed
will be used as final value.
Raises:
Error when the value is not compatible with the value spec.
| def custom_apply(
self,
path: object_utils.KeyPath,
value_spec: pg_typing.ValueSpec,
allow_partial: bool,
child_transform: Optional[
Callable[[object_utils.KeyPath, pg_typing.Field, Any], Any]] = None
) -> Tuple[bool, Any]:
"""Custom apply on a value based on its original value spec.
This implements ``pg.pg_typing.CustomTyping``, allowing a pure symbolic
value to be assigned to any field. To customize this behavior, override
this method in subclasses.
Args:
path: KeyPath of current object under its object tree.
value_spec: Original value spec for this field.
allow_partial: Whether allow partial object to be created.
child_transform: Function to transform child node values into their final
values. Transform function is called on leaf nodes first, then on their
parents, recursively.
Returns:
A tuple (proceed_with_standard_apply, value_to_proceed).
If proceed_with_standard_apply is set to False, value_to_proceed
will be used as final value.
Raises:
Error when the value is not compatible with the value spec.
"""
del path, value_spec, allow_partial, child_transform
return (False, self)
| (self, path: pyglove.core.object_utils.value_location.KeyPath, value_spec: pyglove.core.typing.class_schema.ValueSpec, allow_partial: bool, child_transform: Optional[Callable[[pyglove.core.object_utils.value_location.KeyPath, pyglove.core.typing.class_schema.Field, Any], Any]] = None) -> Tuple[bool, Any] | [
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|
40,736 | pyglove.core.symbolic.diff | format | Override format to conditionally print the shared value or the diff. | def format(
self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
**kwargs):
"""Override format to conditionally print the shared value or the diff."""
if not bool(self):
if self.value == Diff.MISSING:
return 'No diff'
# When there is no diff, but the same value needs to be displayed
# we simply return the value.
return object_utils.format(
self.value, compact, verbose, root_indent, **kwargs)
if self.is_leaf:
exclude_keys = kwargs.pop('exclude_keys', None)
exclude_keys = exclude_keys or set()
exclude_keys.add('children')
return super().format(
compact, verbose, root_indent, exclude_keys=exclude_keys, **kwargs)
else:
assert isinstance(self.left, type)
assert isinstance(self.right, type)
if self.left is self.right and issubclass(self.left, list):
return self.children.format(
compact=compact,
verbose=verbose,
root_indent=root_indent,
cls_name='',
bracket_type=object_utils.BracketType.SQUARE)
if self.left is self.right:
cls_name = self.left.__name__
else:
cls_name = f'{self.left.__name__}|{self.right.__name__}'
return self.children.format(
compact=compact,
verbose=verbose,
root_indent=root_indent,
cls_name=cls_name,
bracket_type=object_utils.BracketType.ROUND)
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|
40,749 | pyglove.core.symbolic.diff | sym_eq | Override symbolic equality. | def sym_eq(self, other: Any):
"""Override symbolic equality."""
if super().sym_eq(other):
return True
if not bool(self):
return base.eq(self.left, other)
| (self, other: Any) | [
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|
40,773 | pyglove.core.object_utils.docstr_utils | DocStr | Docstring. | class DocStr:
"""Docstring."""
style: DocStrStyle
short_description: Optional[str]
long_description: Optional[str]
examples: List[DocStrExample]
args: Dict[str, DocStrArgument]
returns: Optional[DocStrReturns]
raises: List[DocStrRaises]
blank_after_short_description: bool = True
@classmethod
def parse(cls, text: str, style: Optional[DocStrStyle] = None) -> 'DocStr':
"""Parses a docstring."""
result = docstring_parser.parse(text, _to_parser_style(style))
return cls(
style=_from_parser_style(result.style),
short_description=result.short_description,
long_description=result.long_description,
examples=[
DocStrExample(description=e.description)
for e in result.examples
],
args={ # pylint: disable=g-complex-comprehension
p.arg_name: DocStrArgument(
name=p.arg_name, description=p.description,
type_name=p.type_name, default=p.default,
is_optional=p.is_optional)
for p in result.params
},
returns=DocStrReturns( # pylint: disable=g-long-ternary
name=result.returns.return_name,
description=result.returns.description,
is_yield=result.returns.is_generator) if result.returns else None,
raises=[
DocStrRaises(type_name=r.type_name, description=r.description)
for r in result.raises
],
blank_after_short_description=result.blank_after_short_description)
| (style: pyglove.core.object_utils.docstr_utils.DocStrStyle, short_description: Optional[str], long_description: Optional[str], examples: List[pyglove.core.object_utils.docstr_utils.DocStrExample], args: Dict[str, pyglove.core.object_utils.docstr_utils.DocStrArgument], returns: Optional[pyglove.core.object_utils.docstr_utils.DocStrReturns], raises: List[pyglove.core.object_utils.docstr_utils.DocStrRaises], blank_after_short_description: bool = True) -> None | [
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|
40,774 | pyglove.core.object_utils.docstr_utils | __eq__ | null | # Copyright 2023 The PyGlove Authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""Utilities for working with docstrs."""
import dataclasses
import enum
from typing import Any, Dict, List, Optional
import docstring_parser
class DocStrStyle(enum.Enum):
"""Docstring style."""
REST = 1
GOOGLE = 2
NUMPYDOC = 3
EPYDOC = 4
| (self, other) | [
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|
40,777 | pyglove.core.typing.class_schema | Field | Class that represents the definition of one or a group of attributes.
``Field`` is held by a :class:`pyglove.Schema` object for defining the
name(s), the validation and transformation rules on its/their value(s) for a
single symbolic attribute or a set of symbolic attributes.
A ``Field`` is defined by a tuple of 4 items::
(key specification, value specification, doc string, field metadata)
For example::
(pg.typing.StrKey('foo.*'),
pg.typing.Int(),
'Attributes with foo',
{'user_data': 'bar'})
The key specification (or ``KeySpec``, class :class:`pyglove.KeySpec`) and
value specification (or ``ValueSpec``, class :class:`pyglove.ValueSpec`) are
required, while the doc string and the field metadata are optional. The
``KeySpec`` defines acceptable identifiers for this field, and the
``ValueSpec`` defines the attribute's value type, its default value,
validation rules and etc. The doc string serves as the description for the
field, and the field metadata can be used for attribute-based code generation.
``Field`` supports extension, which allows the subclass to add more
restrictions to a field inherited from the base class, or override its default
value. A field can be frozen if subclasses can no longer extend it.
See :class:`pyglove.KeySpec` and :class:`pyglove.ValueSpec` for details.
| class Field(object_utils.Formattable, object_utils.JSONConvertible):
"""Class that represents the definition of one or a group of attributes.
``Field`` is held by a :class:`pyglove.Schema` object for defining the
name(s), the validation and transformation rules on its/their value(s) for a
single symbolic attribute or a set of symbolic attributes.
A ``Field`` is defined by a tuple of 4 items::
(key specification, value specification, doc string, field metadata)
For example::
(pg.typing.StrKey('foo.*'),
pg.typing.Int(),
'Attributes with foo',
{'user_data': 'bar'})
The key specification (or ``KeySpec``, class :class:`pyglove.KeySpec`) and
value specification (or ``ValueSpec``, class :class:`pyglove.ValueSpec`) are
required, while the doc string and the field metadata are optional. The
``KeySpec`` defines acceptable identifiers for this field, and the
``ValueSpec`` defines the attribute's value type, its default value,
validation rules and etc. The doc string serves as the description for the
field, and the field metadata can be used for attribute-based code generation.
``Field`` supports extension, which allows the subclass to add more
restrictions to a field inherited from the base class, or override its default
value. A field can be frozen if subclasses can no longer extend it.
See :class:`pyglove.KeySpec` and :class:`pyglove.ValueSpec` for details.
"""
__serialization_key__ = 'pyglove.typing.Field'
def __init__(
self,
key_spec: Union[KeySpec, str],
value_spec: ValueSpec,
description: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None):
"""Constructor.
Args:
key_spec: Key specification of the field. Can be a string or a KeySpec
instance.
value_spec: Value specification of the field.
description: Description of the field.
metadata: A dict of objects as metadata for the field.
Raises:
ValueError: metadata is not a dict.
"""
if isinstance(key_spec, str):
key_spec = KeySpec.from_str(key_spec)
assert isinstance(key_spec, KeySpec), key_spec
self._key = key_spec
self._value = value_spec
self._description = description
if metadata and not isinstance(metadata, dict):
raise ValueError('metadata must be a dict.')
self._metadata = metadata or {}
@classmethod
def from_annotation(
cls,
key: Union[str, KeySpec],
annotation: Any,
description: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None,
auto_typing=True) -> 'Field':
"""Gets a Field from annotation."""
del key, annotation, description, metadata, auto_typing
assert False, 'Overridden in `annotation_conversion.py`.'
@property
def description(self) -> Optional[str]:
"""Description of this field."""
return self._description
def set_description(self, description: str) -> None:
"""Sets the description for this field."""
self._description = description
@property
def key(self) -> KeySpec:
"""Key specification of this field."""
return self._key
@property
def value(self) -> ValueSpec:
"""Value specification of this field."""
return self._value
@property
def annotation(self) -> Any:
"""Type annotation for this field."""
return self._value.annotation
@property
def metadata(self) -> Dict[str, Any]:
"""Metadata of this field.
Metadata is defined as a dict type, so we can add multiple annotations
to a field.
userdata = field.metadata.get('userdata', None):
Returns:
Metadata of this field as a dict.
"""
return self._metadata
def extend(self, base_field: 'Field') -> 'Field':
"""Extend current field based on a base field."""
self.key.extend(base_field.key)
self.value.extend(base_field.value)
if not self._description:
self._description = base_field.description
if base_field.metadata:
metadata = copy.copy(base_field.metadata)
metadata.update(self.metadata)
self._metadata = metadata
return self
def apply(
self,
value: Any,
allow_partial: bool = False,
transform_fn: Optional[Callable[
[object_utils.KeyPath, 'Field', Any], Any]] = None,
root_path: Optional[object_utils.KeyPath] = None) -> Any:
"""Apply current field to a value, which validate and complete the value.
Args:
value: Value to validate against this spec.
allow_partial: Whether partial value is allowed. This is for dict or
nested dict values.
transform_fn: Function to transform applied value into final value.
root_path: Key path for root.
Returns:
final value.
When allow_partial is set to False (default), only fully qualified value
is acceptable. When allow_partial is set to True, missing fields will
be placeheld using MISSING_VALUE.
Raises:
KeyError: if additional key is found in value, or required key is missing
and allow_partial is set to False.
TypeError: if type of value is not the same as spec required.
ValueError: if value is not acceptable, or value is MISSING_VALUE while
allow_partial is set to False.
"""
value = self._value.apply(
value,
allow_partial=allow_partial,
child_transform=transform_fn,
root_path=root_path)
if transform_fn:
value = transform_fn(root_path, self, value)
return value
@property
def default_value(self) -> Any:
"""Returns the default value."""
return self._value.default
@property
def frozen(self) -> bool:
"""Returns True if current field's value is frozen."""
return self._value.frozen
def format(self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
**kwargs) -> str:
"""Format this field into a string."""
description = self._description
if not verbose and self._description and len(self._description) > 20:
description = self._description[:20] + '...'
metadata = object_utils.format(
self._metadata,
compact=compact,
verbose=verbose,
root_indent=root_indent + 1,
**kwargs)
if not verbose and len(metadata) > 24:
metadata = '{...}'
attr_str = object_utils.kvlist_str([
('key', self._key, None),
('value', self._value.format(
compact=compact,
verbose=verbose,
root_indent=root_indent + 1,
**kwargs), None),
('description', object_utils.quote_if_str(description), None),
('metadata', metadata, '{}')
])
return f'Field({attr_str})'
def to_json(self, **kwargs: Any) -> Dict[str, Any]:
return self.to_json_dict(
fields=dict(
key_spec=(self._key, None),
value_spec=(self._value, None),
description=(self._description, None),
metadata=(self._metadata, {}),
),
exclude_default=True,
**kwargs,
)
def __eq__(self, other: Any) -> bool:
"""Operator==."""
if self is other:
return True
return (isinstance(other, self.__class__) and self.key == other.key and
self.value == other.value and
self.description == other.description and
self.metadata == other.metadata)
def __ne__(self, other: Any) -> bool:
"""Operator!=."""
return not self.__eq__(other)
| (key_spec: Union[pyglove.core.typing.class_schema.KeySpec, str], value_spec: pyglove.core.typing.class_schema.ValueSpec, description: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) | [
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|
40,779 | pyglove.core.typing.class_schema | __eq__ | Operator==. | def __eq__(self, other: Any) -> bool:
"""Operator==."""
if self is other:
return True
return (isinstance(other, self.__class__) and self.key == other.key and
self.value == other.value and
self.description == other.description and
self.metadata == other.metadata)
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|
40,780 | pyglove.core.typing.class_schema | __init__ | Constructor.
Args:
key_spec: Key specification of the field. Can be a string or a KeySpec
instance.
value_spec: Value specification of the field.
description: Description of the field.
metadata: A dict of objects as metadata for the field.
Raises:
ValueError: metadata is not a dict.
| def __init__(
self,
key_spec: Union[KeySpec, str],
value_spec: ValueSpec,
description: Optional[str] = None,
metadata: Optional[Dict[str, Any]] = None):
"""Constructor.
Args:
key_spec: Key specification of the field. Can be a string or a KeySpec
instance.
value_spec: Value specification of the field.
description: Description of the field.
metadata: A dict of objects as metadata for the field.
Raises:
ValueError: metadata is not a dict.
"""
if isinstance(key_spec, str):
key_spec = KeySpec.from_str(key_spec)
assert isinstance(key_spec, KeySpec), key_spec
self._key = key_spec
self._value = value_spec
self._description = description
if metadata and not isinstance(metadata, dict):
raise ValueError('metadata must be a dict.')
self._metadata = metadata or {}
| (self, key_spec: Union[pyglove.core.typing.class_schema.KeySpec, str], value_spec: pyglove.core.typing.class_schema.ValueSpec, description: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None) | [
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|
40,781 | pyglove.core.typing.class_schema | __ne__ | Operator!=. | def __ne__(self, other: Any) -> bool:
"""Operator!=."""
return not self.__eq__(other)
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|
40,785 | pyglove.core.typing.class_schema | apply | Apply current field to a value, which validate and complete the value.
Args:
value: Value to validate against this spec.
allow_partial: Whether partial value is allowed. This is for dict or
nested dict values.
transform_fn: Function to transform applied value into final value.
root_path: Key path for root.
Returns:
final value.
When allow_partial is set to False (default), only fully qualified value
is acceptable. When allow_partial is set to True, missing fields will
be placeheld using MISSING_VALUE.
Raises:
KeyError: if additional key is found in value, or required key is missing
and allow_partial is set to False.
TypeError: if type of value is not the same as spec required.
ValueError: if value is not acceptable, or value is MISSING_VALUE while
allow_partial is set to False.
| def apply(
self,
value: Any,
allow_partial: bool = False,
transform_fn: Optional[Callable[
[object_utils.KeyPath, 'Field', Any], Any]] = None,
root_path: Optional[object_utils.KeyPath] = None) -> Any:
"""Apply current field to a value, which validate and complete the value.
Args:
value: Value to validate against this spec.
allow_partial: Whether partial value is allowed. This is for dict or
nested dict values.
transform_fn: Function to transform applied value into final value.
root_path: Key path for root.
Returns:
final value.
When allow_partial is set to False (default), only fully qualified value
is acceptable. When allow_partial is set to True, missing fields will
be placeheld using MISSING_VALUE.
Raises:
KeyError: if additional key is found in value, or required key is missing
and allow_partial is set to False.
TypeError: if type of value is not the same as spec required.
ValueError: if value is not acceptable, or value is MISSING_VALUE while
allow_partial is set to False.
"""
value = self._value.apply(
value,
allow_partial=allow_partial,
child_transform=transform_fn,
root_path=root_path)
if transform_fn:
value = transform_fn(root_path, self, value)
return value
| (self, value: Any, allow_partial: bool = False, transform_fn: Optional[Callable[[pyglove.core.object_utils.value_location.KeyPath, pyglove.core.typing.class_schema.Field, Any], Any]] = None, root_path: Optional[pyglove.core.object_utils.value_location.KeyPath] = None) -> Any | [
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|
40,786 | pyglove.core.typing.class_schema | extend | Extend current field based on a base field. | def extend(self, base_field: 'Field') -> 'Field':
"""Extend current field based on a base field."""
self.key.extend(base_field.key)
self.value.extend(base_field.value)
if not self._description:
self._description = base_field.description
if base_field.metadata:
metadata = copy.copy(base_field.metadata)
metadata.update(self.metadata)
self._metadata = metadata
return self
| (self, base_field: pyglove.core.typing.class_schema.Field) -> pyglove.core.typing.class_schema.Field | [
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]
|
40,787 | pyglove.core.typing.class_schema | format | Format this field into a string. | def format(self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
**kwargs) -> str:
"""Format this field into a string."""
description = self._description
if not verbose and self._description and len(self._description) > 20:
description = self._description[:20] + '...'
metadata = object_utils.format(
self._metadata,
compact=compact,
verbose=verbose,
root_indent=root_indent + 1,
**kwargs)
if not verbose and len(metadata) > 24:
metadata = '{...}'
attr_str = object_utils.kvlist_str([
('key', self._key, None),
('value', self._value.format(
compact=compact,
verbose=verbose,
root_indent=root_indent + 1,
**kwargs), None),
('description', object_utils.quote_if_str(description), None),
('metadata', metadata, '{}')
])
return f'Field({attr_str})'
| (self, compact: bool = False, verbose: bool = True, root_indent: int = 0, **kwargs) -> str | [
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|
40,788 | pyglove.core.typing.annotation_conversion | _field_from_annotation | Creates a field from Python annotation. | def _field_from_annotation(
key: typing.Union[str, class_schema.KeySpec],
annotation: typing.Any,
description: typing.Optional[str] = None,
metadata: typing.Optional[typing.Dict[str, typing.Any]] = None,
auto_typing=True,
) -> class_schema.Field:
"""Creates a field from Python annotation."""
if isinstance(annotation, annotated.Annotated):
field_spec = (
key, annotation.value_spec, annotation.docstring, annotation.metadata)
elif _Annotated and typing.get_origin(annotation) is _Annotated:
type_args = typing.get_args(annotation)
assert len(type_args) > 1, (annotation, type_args)
field_spec = tuple([key] + list(type_args))
else:
field_spec = (key, annotation, description, metadata or {})
return class_schema.create_field(
field_spec,
auto_typing=auto_typing,
accept_value_as_annotation=False)
| (key: Union[str, pyglove.core.typing.class_schema.KeySpec], annotation: Any, description: Optional[str] = None, metadata: Optional[Dict[str, Any]] = None, auto_typing=True) -> pyglove.core.typing.class_schema.Field | [
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|
40,789 | pyglove.core.typing.class_schema | set_description | Sets the description for this field. | def set_description(self, description: str) -> None:
"""Sets the description for this field."""
self._description = description
| (self, description: str) -> NoneType | [
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|
40,790 | pyglove.core.typing.class_schema | to_json | null | def to_json(self, **kwargs: Any) -> Dict[str, Any]:
return self.to_json_dict(
fields=dict(
key_spec=(self._key, None),
value_spec=(self._value, None),
description=(self._description, None),
metadata=(self._metadata, {}),
),
exclude_default=True,
**kwargs,
)
| (self, **kwargs: Any) -> Dict[str, Any] | [
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|
40,791 | pyglove.core.symbolic.base | FieldUpdate | Class that describes an update to a field in an object tree. | class FieldUpdate(object_utils.Formattable):
"""Class that describes an update to a field in an object tree."""
def __init__(self,
path: object_utils.KeyPath,
target: 'Symbolic',
field: Optional[pg_typing.Field],
old_value: Any,
new_value: Any):
"""Constructor.
Args:
path: KeyPath of the field that is updated.
target: Parent of updated field.
field: Specification of the updated field.
old_value: Old value of the field.
new_value: New value of the field.
"""
self.path = path
self.target = target
self.field = field
self.old_value = old_value
self.new_value = new_value
def format(self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
*,
python_format: bool = False,
hide_default_values: bool = False,
hide_missing_values: bool = False,
**kwargs) -> str:
"""Formats this object."""
kwargs.update({
'python_format': python_format,
'hide_default_values': hide_default_values,
'hide_missing_values': hide_missing_values,
})
details = object_utils.kvlist_str([
('parent_path', self.target.sym_path, None),
('path', self.path.path, None),
('old_value', object_utils.format(
self.old_value, compact, verbose, root_indent + 1, **kwargs),
object_utils.MISSING_VALUE),
('new_value',
object_utils.format(
self.new_value, compact, verbose, root_indent + 1, **kwargs),
object_utils.MISSING_VALUE),
])
return f'{self.__class__.__name__}({details})'
def __eq__(self, other: Any) -> bool:
"""Operator ==."""
if not isinstance(other, self.__class__):
return False
return (self.path == other.path and self.target is other.target and
self.field is other.field and self.old_value == other.old_value and
self.new_value == other.new_value)
def __ne__(self, other: Any) -> bool:
"""Operator !=."""
return not self.__eq__(other)
| (path: pyglove.core.object_utils.value_location.KeyPath, target: 'Symbolic', field: Optional[pyglove.core.typing.class_schema.Field], old_value: Any, new_value: Any) | [
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|
40,792 | pyglove.core.symbolic.base | __eq__ | Operator ==. | def __eq__(self, other: Any) -> bool:
"""Operator ==."""
if not isinstance(other, self.__class__):
return False
return (self.path == other.path and self.target is other.target and
self.field is other.field and self.old_value == other.old_value and
self.new_value == other.new_value)
| (self, other: Any) -> bool | [
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|
40,793 | pyglove.core.symbolic.base | __init__ | Constructor.
Args:
path: KeyPath of the field that is updated.
target: Parent of updated field.
field: Specification of the updated field.
old_value: Old value of the field.
new_value: New value of the field.
| def __init__(self,
path: object_utils.KeyPath,
target: 'Symbolic',
field: Optional[pg_typing.Field],
old_value: Any,
new_value: Any):
"""Constructor.
Args:
path: KeyPath of the field that is updated.
target: Parent of updated field.
field: Specification of the updated field.
old_value: Old value of the field.
new_value: New value of the field.
"""
self.path = path
self.target = target
self.field = field
self.old_value = old_value
self.new_value = new_value
| (self, path: pyglove.core.object_utils.value_location.KeyPath, target: pyglove.core.symbolic.base.Symbolic, field: Optional[pyglove.core.typing.class_schema.Field], old_value: Any, new_value: Any) | [
0.04931296408176422,
-0.03184647113084793,
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|
40,798 | pyglove.core.symbolic.base | format | Formats this object. | def format(self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
*,
python_format: bool = False,
hide_default_values: bool = False,
hide_missing_values: bool = False,
**kwargs) -> str:
"""Formats this object."""
kwargs.update({
'python_format': python_format,
'hide_default_values': hide_default_values,
'hide_missing_values': hide_missing_values,
})
details = object_utils.kvlist_str([
('parent_path', self.target.sym_path, None),
('path', self.path.path, None),
('old_value', object_utils.format(
self.old_value, compact, verbose, root_indent + 1, **kwargs),
object_utils.MISSING_VALUE),
('new_value',
object_utils.format(
self.new_value, compact, verbose, root_indent + 1, **kwargs),
object_utils.MISSING_VALUE),
])
return f'{self.__class__.__name__}({details})'
| (self, compact: bool = False, verbose: bool = True, root_indent: int = 0, *, python_format: bool = False, hide_default_values: bool = False, hide_missing_values: bool = False, **kwargs) -> str | [
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|
40,799 | pyglove.core.object_utils.common_traits | Formattable | Interface for classes whose instances can be pretty-formatted.
This interface overrides the default ``__repr__`` and ``__str__`` method, thus
all ``Formattable`` objects can be printed nicely.
All symbolic types implement this interface.
| class Formattable(metaclass=abc.ABCMeta):
"""Interface for classes whose instances can be pretty-formatted.
This interface overrides the default ``__repr__`` and ``__str__`` method, thus
all ``Formattable`` objects can be printed nicely.
All symbolic types implement this interface.
"""
# Additional format keyword arguments for `__str__`.
__str_format_kwargs__ = dict(compact=False, verbose=True)
# Additional format keyword arguments for `__repr__`.
__repr_format_kwargs__ = dict(compact=True)
@abc.abstractmethod
def format(self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
**kwargs) -> str:
"""Formats this object into a string representation.
Args:
compact: If True, this object will be formatted into a single line.
verbose: If True, this object will be formatted with verbosity.
Subclasses should define `verbosity` on their own.
root_indent: The start indent level for this object if the output is a
multi-line string.
**kwargs: Subclass specific keyword arguments.
Returns:
A string of formatted object.
"""
def __str__(self) -> str:
"""Returns the full (maybe multi-line) representation of this object."""
kwargs = dict(self.__str_format_kwargs__)
kwargs.update(thread_local.thread_local_kwargs(_TLS_STR_FORMAT_KWARGS))
return self._maybe_quote(self.format(**kwargs), **kwargs)
def __repr__(self) -> str:
"""Returns a single-line representation of this object."""
kwargs = dict(self.__repr_format_kwargs__)
kwargs.update(thread_local.thread_local_kwargs(_TLS_REPR_FORMAT_KWARGS))
return self._maybe_quote(self.format(**kwargs), **kwargs)
def _maybe_quote(
self,
s: str,
*,
compact: bool = False,
root_indent: int = 0,
markdown: bool = False,
**kwargs
) -> str:
"""Maybe quote the formatted string with markdown."""
del kwargs
if not markdown or root_indent > 0:
return s
if compact:
return f'`{s}`'
else:
return f'\n```\n{s}\n```\n'
| () | [
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|
40,803 | pyglove.core.object_utils.common_traits | format | Formats this object into a string representation.
Args:
compact: If True, this object will be formatted into a single line.
verbose: If True, this object will be formatted with verbosity.
Subclasses should define `verbosity` on their own.
root_indent: The start indent level for this object if the output is a
multi-line string.
**kwargs: Subclass specific keyword arguments.
Returns:
A string of formatted object.
| @abc.abstractmethod
def format(self,
compact: bool = False,
verbose: bool = True,
root_indent: int = 0,
**kwargs) -> str:
"""Formats this object into a string representation.
Args:
compact: If True, this object will be formatted into a single line.
verbose: If True, this object will be formatted with verbosity.
Subclasses should define `verbosity` on their own.
root_indent: The start indent level for this object if the output is a
multi-line string.
**kwargs: Subclass specific keyword arguments.
Returns:
A string of formatted object.
"""
| (self, compact: bool = False, verbose: bool = True, root_indent: int = 0, **kwargs) -> str | [
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|
40,804 | pyglove.core.symbolic.functor | Functor | Symbolic functions (Functors).
A symbolic function is a symbolic class with a ``__call__`` method, whose
arguments can be bound partially, incrementally bound by attribute
assignment, or provided at call time.
Another useful trait is that a symbolic function is serializable, when
its definition is imported by the target program and its arguments are also
serializable. Therefore, it is very handy to move a symbolic function
around in distributed scenarios.
Symbolic functions can be created from regular function via
:func:`pyglove.functor`::
# Create a functor class using @pg.functor decorator.
@pg.functor([
('a', pg.typing.Int(), 'Argument a'),
# No field specification for 'b', which will be treated as any type.
])
def sum(a, b=1, *args, **kwargs):
return a + b + sum(args + kwargs.values())
sum(1)() # returns 2: prebind a=1, invoke with b=1 (default)
sum(a=1)() # returns 2: same as above.
sum()(1) # returns 2: bind a=1 at call time, b=1(default)
sum(b=2)(1) # returns 3: prebind b=2, invoke with a=1.
sum(b=2)() # wrong: `a` is not provided.
sum(1)(2) # wrong: 'a' is provided multiple times.
sum(1)(2, override_args=True) # ok: override `a` value with 2.
sum()(1, 2, 3, 4) # returns 10: a=1, b=2, *args=[3, 4]
sum(c=4)(1, 2, 3) # returns 10: a=1, b=2, *args=[3], **kwargs={'c': 4}
Or created by subclassing ``pg.Functor``::
class Sum(pg.Functor):
a: int
b: int = 1
def _call(self) -> int:
return self.a + self.b
Usage on subclassed functors is the same as functors created from functions.
| class Functor(pg_object.Object, object_utils.Functor):
"""Symbolic functions (Functors).
A symbolic function is a symbolic class with a ``__call__`` method, whose
arguments can be bound partially, incrementally bound by attribute
assignment, or provided at call time.
Another useful trait is that a symbolic function is serializable, when
its definition is imported by the target program and its arguments are also
serializable. Therefore, it is very handy to move a symbolic function
around in distributed scenarios.
Symbolic functions can be created from regular function via
:func:`pyglove.functor`::
# Create a functor class using @pg.functor decorator.
@pg.functor([
('a', pg.typing.Int(), 'Argument a'),
# No field specification for 'b', which will be treated as any type.
])
def sum(a, b=1, *args, **kwargs):
return a + b + sum(args + kwargs.values())
sum(1)() # returns 2: prebind a=1, invoke with b=1 (default)
sum(a=1)() # returns 2: same as above.
sum()(1) # returns 2: bind a=1 at call time, b=1(default)
sum(b=2)(1) # returns 3: prebind b=2, invoke with a=1.
sum(b=2)() # wrong: `a` is not provided.
sum(1)(2) # wrong: 'a' is provided multiple times.
sum(1)(2, override_args=True) # ok: override `a` value with 2.
sum()(1, 2, 3, 4) # returns 10: a=1, b=2, *args=[3, 4]
sum(c=4)(1, 2, 3) # returns 10: a=1, b=2, *args=[3], **kwargs={'c': 4}
Or created by subclassing ``pg.Functor``::
class Sum(pg.Functor):
a: int
b: int = 1
def _call(self) -> int:
return self.a + self.b
Usage on subclassed functors is the same as functors created from functions.
"""
# Allow assignment on symbolic attributes.
allow_symbolic_assignment = True
# Key for storing override members during call.
_TLS_OVERRIDE_MEMBERS_KEY = '__override_members__'
#
# Customizable class traits.
#
@classmethod
@property
def is_subclassed_functor(cls) -> bool:
"""Returns True if this class is a subclassed Functor."""
return cls.auto_schema
@classmethod
def _update_signatures_based_on_schema(cls):
# Update the return value of subclassed functors.
if cls.is_subclassed_functor: # pylint: disable=using-constant-test
private_call_signature = pg_typing.Signature.from_callable(
cls._call, auto_typing=True
)
if (
len(private_call_signature.args) > 1
or private_call_signature.kwonlyargs
):
raise TypeError(
'`_call` of a subclassed Functor should take no argument. '
f'Encountered: {cls._call}.'
)
cls.__schema__.metadata['returns'] = private_call_signature.return_value
# Update __init_ signature.
init_signature = pg_typing.Signature.from_schema(
cls.__schema__,
name='__init__',
module_name=cls.__module__,
qualname=cls.__qualname__,
)
pseudo_init = init_signature.make_function(['pass'])
# Save the original `Functor.__init__` before overriding it.
if not hasattr(cls, '__orig_init__'):
setattr(cls, '__orig_init__', cls.__init__)
@object_utils.explicit_method_override
@functools.wraps(pseudo_init)
def _init(self, *args, **kwargs):
self.__class__.__orig_init__(self, *args, **kwargs)
setattr(cls, '__init__', _init)
# Update __call__ signature.
call_signature = pg_typing.Signature.from_schema(
cls.__schema__,
name='__call__',
module_name=cls.__module__,
qualname=cls.__qualname__,
is_method=False,
)
setattr(cls, '__signature__', call_signature)
def __new__(cls, *args, **kwargs):
instance = object.__new__(cls)
if flags.should_call_functors_during_init():
instance.__init__(*args, **kwargs)
return instance()
return instance
@object_utils.explicit_method_override
def __init__(
self,
*args,
root_path: Optional[object_utils.KeyPath] = None,
override_args: bool = False,
ignore_extra_args: bool = False,
**kwargs):
"""Constructor.
Args:
*args: prebound positional arguments.
root_path: The symbolic path for current object.
override_args: If True, allows arguments provided during `__call__` to
override existing bound arguments.
ignore_extra_args: If True, unsupported arguments can be passed in
during `__call__` without using them. Otherwise, calling with
unsupported arguments will raise error.
**kwargs: prebound keyword arguments.
Raises:
KeyError: constructor got unexpected arguments.
"""
# NOTE(daiyip): Since Functor is usually late bound (until call time),
# we pass `allow_partial=True` during functor construction.
_ = kwargs.pop('allow_partial', None)
varargs = None
signature = self.__signature__
if len(args) > len(signature.args):
if signature.varargs:
varargs = list(args[len(signature.args) :])
args = args[: len(signature.args)]
else:
arg_phrase = object_utils.auto_plural(len(signature.args), 'argument')
was_phrase = object_utils.auto_plural(len(args), 'was', 'were')
raise TypeError(
f'{signature.id}() takes {len(signature.args)} '
f'positional {arg_phrase} but {len(args)} {was_phrase} given.'
)
bound_kwargs = dict()
for i, v in enumerate(args):
if pg_typing.MISSING_VALUE != v:
bound_kwargs[signature.args[i].name] = v
if varargs is not None:
bound_kwargs[signature.varargs.name] = varargs
for k, v in kwargs.items():
if pg_typing.MISSING_VALUE != v:
if k in bound_kwargs:
raise TypeError(
f'{signature.id}() got multiple values for keyword '
f'argument {k!r}.'
)
bound_kwargs[k] = v
default_args = set()
non_default_args = set(bound_kwargs)
for arg_spec in signature.named_args:
if not arg_spec.value_spec.has_default:
continue
arg_name = arg_spec.name
if arg_name not in non_default_args:
default_args.add(arg_name)
elif bound_kwargs[arg_name] == arg_spec.value_spec.default:
default_args.add(arg_name)
non_default_args.discard(arg_name)
if signature.varargs and not varargs:
default_args.add(signature.varargs.name)
super().__init__(allow_partial=True,
root_path=root_path,
**bound_kwargs)
self._non_default_args = non_default_args
self._default_args = default_args
self._specified_args = set(bound_kwargs)
self._override_args = override_args
self._ignore_extra_args = ignore_extra_args
# For subclassed Functor, we use thread-local storage for storing temporary
# member overrides from the arguments during functor call.
self._tls = threading.local() if self.is_subclassed_functor else None
def _sym_inferred(self, key: str, **kwargs: Any) -> Any:
"""Overrides method to allow member overrides during call."""
if self._tls is not None:
overrides = getattr(self._tls, Functor._TLS_OVERRIDE_MEMBERS_KEY, {})
v = overrides.get(key, pg_typing.MISSING_VALUE)
if pg_typing.MISSING_VALUE != v:
return overrides[key]
return super()._sym_inferred(key, **kwargs)
def _sym_clone(self, deep: bool, memo: Any = None) -> 'Functor':
"""Override to copy bound args."""
other = super()._sym_clone(deep, memo)
# pylint: disable=protected-access
other._non_default_args = set(self._non_default_args)
other._default_args = self._default_args
other._specified_args = self._specified_args
other._override_args = self._override_args
other._ignore_extra_args = self._ignore_extra_args
# pylint: enable=protected-access
return typing.cast(Functor, other)
def _on_change(
self, field_updates: Dict[object_utils.KeyPath, base.FieldUpdate]):
"""Custom handling field change to update bound args."""
for relative_path, update in field_updates.items():
assert relative_path
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|
40,806 | pyglove.core.symbolic.functor | __call__ | Call with late bound arguments.
Args:
*args: list arguments.
**kwargs: keyword arguments.
Returns:
Any.
Raises:
TypeError: got multiple values for arguments or extra argument name.
| def __call__(self, *args, **kwargs) -> Any:
"""Call with late bound arguments.
Args:
*args: list arguments.
**kwargs: keyword arguments.
Returns:
Any.
Raises:
TypeError: got multiple values for arguments or extra argument name.
"""
args, kwargs = self._parse_call_time_overrides(*args, **kwargs)
signature = self.__signature__
if self.is_subclassed_functor:
for arg_spec, arg_value in zip(signature.args, args):
kwargs[arg_spec.name] = arg_value
# Temporarily override members with argument values from the call.
with self._apply_call_time_overrides_to_members(**kwargs):
return_value = self._call()
else:
return_value = self._call(*args, **kwargs)
# Return value check.
if (
signature.return_value
and flags.is_type_check_enabled()
and return_value != pg_typing.MISSING_VALUE
):
return_value = signature.return_value.apply(
return_value, root_path=self.sym_path + 'returns'
)
if flags.is_tracking_origin() and isinstance(return_value, base.Symbolic):
return_value.sym_setorigin(self, 'return')
return return_value
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|
40,809 | pyglove.core.symbolic.functor | __delattr__ | Discard a previously bound argument and reset to its default value. | def __delattr__(self, name: str) -> None:
"""Discard a previously bound argument and reset to its default value."""
del self._sym_attributes[name]
if self.__signature__.get_value_spec(name).has_default:
self._default_args.add(name)
self._specified_args.discard(name)
self._non_default_args.discard(name)
| (self, name: str) -> NoneType | [
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|
40,814 | pyglove.core.symbolic.functor | __init__ | null | @classmethod
def _update_signatures_based_on_schema(cls):
# Update the return value of subclassed functors.
if cls.is_subclassed_functor: # pylint: disable=using-constant-test
private_call_signature = pg_typing.Signature.from_callable(
cls._call, auto_typing=True
)
if (
len(private_call_signature.args) > 1
or private_call_signature.kwonlyargs
):
raise TypeError(
'`_call` of a subclassed Functor should take no argument. '
f'Encountered: {cls._call}.'
)
cls.__schema__.metadata['returns'] = private_call_signature.return_value
# Update __init_ signature.
init_signature = pg_typing.Signature.from_schema(
cls.__schema__,
name='__init__',
module_name=cls.__module__,
qualname=cls.__qualname__,
)
pseudo_init = init_signature.make_function(['pass'])
# Save the original `Functor.__init__` before overriding it.
if not hasattr(cls, '__orig_init__'):
setattr(cls, '__orig_init__', cls.__init__)
@object_utils.explicit_method_override
@functools.wraps(pseudo_init)
def _init(self, *args, **kwargs):
self.__class__.__orig_init__(self, *args, **kwargs)
setattr(cls, '__init__', _init)
# Update __call__ signature.
call_signature = pg_typing.Signature.from_schema(
cls.__schema__,
name='__call__',
module_name=cls.__module__,
qualname=cls.__qualname__,
is_method=False,
)
setattr(cls, '__signature__', call_signature)
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|
40,816 | pyglove.core.symbolic.functor | __new__ | null | def __new__(cls, *args, **kwargs):
instance = object.__new__(cls)
if flags.should_call_functors_during_init():
instance.__init__(*args, **kwargs)
return instance()
return instance
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|
40,817 | pyglove.core.symbolic.functor | __init__ | Constructor.
Args:
*args: prebound positional arguments.
root_path: The symbolic path for current object.
override_args: If True, allows arguments provided during `__call__` to
override existing bound arguments.
ignore_extra_args: If True, unsupported arguments can be passed in
during `__call__` without using them. Otherwise, calling with
unsupported arguments will raise error.
**kwargs: prebound keyword arguments.
Raises:
KeyError: constructor got unexpected arguments.
| @object_utils.explicit_method_override
def __init__(
self,
*args,
root_path: Optional[object_utils.KeyPath] = None,
override_args: bool = False,
ignore_extra_args: bool = False,
**kwargs):
"""Constructor.
Args:
*args: prebound positional arguments.
root_path: The symbolic path for current object.
override_args: If True, allows arguments provided during `__call__` to
override existing bound arguments.
ignore_extra_args: If True, unsupported arguments can be passed in
during `__call__` without using them. Otherwise, calling with
unsupported arguments will raise error.
**kwargs: prebound keyword arguments.
Raises:
KeyError: constructor got unexpected arguments.
"""
# NOTE(daiyip): Since Functor is usually late bound (until call time),
# we pass `allow_partial=True` during functor construction.
_ = kwargs.pop('allow_partial', None)
varargs = None
signature = self.__signature__
if len(args) > len(signature.args):
if signature.varargs:
varargs = list(args[len(signature.args) :])
args = args[: len(signature.args)]
else:
arg_phrase = object_utils.auto_plural(len(signature.args), 'argument')
was_phrase = object_utils.auto_plural(len(args), 'was', 'were')
raise TypeError(
f'{signature.id}() takes {len(signature.args)} '
f'positional {arg_phrase} but {len(args)} {was_phrase} given.'
)
bound_kwargs = dict()
for i, v in enumerate(args):
if pg_typing.MISSING_VALUE != v:
bound_kwargs[signature.args[i].name] = v
if varargs is not None:
bound_kwargs[signature.varargs.name] = varargs
for k, v in kwargs.items():
if pg_typing.MISSING_VALUE != v:
if k in bound_kwargs:
raise TypeError(
f'{signature.id}() got multiple values for keyword '
f'argument {k!r}.'
)
bound_kwargs[k] = v
default_args = set()
non_default_args = set(bound_kwargs)
for arg_spec in signature.named_args:
if not arg_spec.value_spec.has_default:
continue
arg_name = arg_spec.name
if arg_name not in non_default_args:
default_args.add(arg_name)
elif bound_kwargs[arg_name] == arg_spec.value_spec.default:
default_args.add(arg_name)
non_default_args.discard(arg_name)
if signature.varargs and not varargs:
default_args.add(signature.varargs.name)
super().__init__(allow_partial=True,
root_path=root_path,
**bound_kwargs)
self._non_default_args = non_default_args
self._default_args = default_args
self._specified_args = set(bound_kwargs)
self._override_args = override_args
self._ignore_extra_args = ignore_extra_args
# For subclassed Functor, we use thread-local storage for storing temporary
# member overrides from the arguments during functor call.
self._tls = threading.local() if self.is_subclassed_functor else None
| (self, *args, root_path: Optional[pyglove.core.object_utils.value_location.KeyPath] = None, override_args: bool = False, ignore_extra_args: bool = False, **kwargs) | [
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|
40,822 | pyglove.core.symbolic.functor | _apply_call_time_overrides_to_members | Overrides member values within the scope. | def _on_change(
self, field_updates: Dict[object_utils.KeyPath, base.FieldUpdate]):
"""Custom handling field change to update bound args."""
for relative_path, update in field_updates.items():
assert relative_path
if len(relative_path) != 1:
continue
arg_name = str(relative_path)
if update.field.default_value == update.new_value:
if update.field.value.has_default:
self._default_args.add(arg_name)
self._non_default_args.discard(arg_name)
else:
self._default_args.discard(arg_name)
self._non_default_args.add(arg_name)
if update.new_value == pg_typing.MISSING_VALUE:
self._specified_args.discard(arg_name)
else:
self._specified_args.add(arg_name)
| (self, **kwargs) | [
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|
40,823 | pyglove.core.symbolic.functor | _call | Actual function logic. Subclasses should implement this method. | def _call(self, *args, **kwargs) -> Callable: # pylint: disable=g-bare-generic
"""Actual function logic. Subclasses should implement this method."""
raise NotImplementedError()
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|
40,829 | pyglove.core.symbolic.functor | _on_change | Custom handling field change to update bound args. | def _on_change(
self, field_updates: Dict[object_utils.KeyPath, base.FieldUpdate]):
"""Custom handling field change to update bound args."""
for relative_path, update in field_updates.items():
assert relative_path
if len(relative_path) != 1:
continue
arg_name = str(relative_path)
if update.field.default_value == update.new_value:
if update.field.value.has_default:
self._default_args.add(arg_name)
self._non_default_args.discard(arg_name)
else:
self._default_args.discard(arg_name)
self._non_default_args.add(arg_name)
if update.new_value == pg_typing.MISSING_VALUE:
self._specified_args.discard(arg_name)
else:
self._specified_args.add(arg_name)
| (self, field_updates: Dict[pyglove.core.object_utils.value_location.KeyPath, pyglove.core.symbolic.base.FieldUpdate]) | [
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|
40,833 | pyglove.core.symbolic.functor | _parse_call_time_overrides | Parses positional and keyword arguments from call-time overrides. | def _parse_call_time_overrides(
self, *args, **kwargs
) -> Tuple[List[Any], Dict[str, Any]]:
"""Parses positional and keyword arguments from call-time overrides."""
override_args = kwargs.pop('override_args', self._override_args)
ignore_extra_args = kwargs.pop('ignore_extra_args', self._ignore_extra_args)
signature = self.__signature__
if len(args) > len(signature.args) and not signature.has_varargs:
if ignore_extra_args:
args = args[: len(signature.args)]
else:
arg_phrase = object_utils.auto_plural(len(signature.args), 'argument')
was_phrase = object_utils.auto_plural(len(args), 'was', 'were')
raise TypeError(
f'{signature.id}() takes {len(signature.args)} '
f'positional {arg_phrase} but {len(args)} {was_phrase} given.'
)
keyword_args = {
k: v for k, v in self._sym_attributes.items()
if k in self._specified_args
}
assert len(keyword_args) == len(self._specified_args)
# Work out varargs when positional arguments are provided.
varargs = None
if signature.has_varargs:
varargs = list(args[len(signature.args) :])
if flags.is_type_check_enabled():
varargs = [
signature.varargs.value_spec.apply(
v, root_path=self.sym_path + signature.varargs.name
)
for v in varargs
]
args = args[: len(signature.args)]
# Convert positional arguments to keyword arguments so we can map them back
# later.
for i in range(len(args)):
arg_spec = signature.args[i]
arg_name = arg_spec.name
if arg_name in self._specified_args:
if not override_args:
raise TypeError(
f'{signature.id}() got new value for argument {arg_name!r} '
f"from position {i}, but 'override_args' is set to False. "
f'Old value: {keyword_args[arg_name]!r}, new value: {args[i]!r}.'
)
arg_value = args[i]
if flags.is_type_check_enabled():
arg_value = arg_spec.value_spec.apply(
arg_value, root_path=self.sym_path + arg_name)
keyword_args[arg_name] = arg_value
for arg_name, arg_value in kwargs.items():
if arg_name in self._specified_args:
if not override_args:
raise TypeError(
f'{signature.id}() got new value for argument {arg_name!r} '
"from keyword argument, while 'override_args' is set to "
f'False. Old value: {keyword_args[arg_name]!r}, '
f'new value: {arg_value!r}.'
)
arg_spec = signature.get_value_spec(arg_name)
if arg_spec and flags.is_type_check_enabled():
arg_value = arg_spec.apply(
arg_value, root_path=self.sym_path + arg_name)
keyword_args[arg_name] = arg_value
elif not ignore_extra_args:
raise TypeError(
f'{signature.id}() got an unexpected keyword argument {arg_name!r}.'
)
# Use positional arguments if possible. This allows us to handle varargs
# with simplicity.
list_args = []
missing_required_arg_names = []
for arg in signature.args:
if arg.name in keyword_args:
list_args.append(keyword_args[arg.name])
del keyword_args[arg.name]
elif arg.value_spec.default != pg_typing.MISSING_VALUE:
list_args.append(arg.value_spec.default)
else:
missing_required_arg_names.append(arg.name)
if missing_required_arg_names:
arg_phrase = object_utils.auto_plural(
len(missing_required_arg_names), 'argument')
args_str = object_utils.comma_delimited_str(missing_required_arg_names)
raise TypeError(
f'{signature.id}() missing {len(missing_required_arg_names)} '
f'required positional {arg_phrase}: {args_str}.'
)
if signature.has_varargs:
prebound_varargs = keyword_args.pop(signature.varargs.name, None)
varargs = varargs or prebound_varargs
if varargs:
list_args.extend(varargs)
return list_args, keyword_args
| (self, *args, **kwargs) -> Tuple[List[Any], Dict[str, Any]] | [
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|
40,838 | pyglove.core.symbolic.functor | _sym_clone | Override to copy bound args. | def _sym_clone(self, deep: bool, memo: Any = None) -> 'Functor':
"""Override to copy bound args."""
other = super()._sym_clone(deep, memo)
# pylint: disable=protected-access
other._non_default_args = set(self._non_default_args)
other._default_args = self._default_args
other._specified_args = self._specified_args
other._override_args = self._override_args
other._ignore_extra_args = self._ignore_extra_args
# pylint: enable=protected-access
return typing.cast(Functor, other)
| (self, deep: bool, memo: Optional[Any] = None) -> pyglove.core.symbolic.functor.Functor | [
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|
40,840 | pyglove.core.symbolic.functor | _sym_inferred | Overrides method to allow member overrides during call. | def _sym_inferred(self, key: str, **kwargs: Any) -> Any:
"""Overrides method to allow member overrides during call."""
if self._tls is not None:
overrides = getattr(self._tls, Functor._TLS_OVERRIDE_MEMBERS_KEY, {})
v = overrides.get(key, pg_typing.MISSING_VALUE)
if pg_typing.MISSING_VALUE != v:
return overrides[key]
return super()._sym_inferred(key, **kwargs)
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|
40,841 | pyglove.core.symbolic.functor | _sym_missing | Returns missing values for Functor.
Semantically unbound arguments are not missing, thus we only return partial
bound arguments in `sym_missing`. As a result, a functor is partial only
when any of its bound arguments is partial.
Returns:
A dict of missing key (or path) to missing value.
| def _sym_missing(self) -> Dict[str, Any]:
"""Returns missing values for Functor.
Semantically unbound arguments are not missing, thus we only return partial
bound arguments in `sym_missing`. As a result, a functor is partial only
when any of its bound arguments is partial.
Returns:
A dict of missing key (or path) to missing value.
"""
missing = dict()
for k, v in self._sym_attributes.items():
if pg_typing.MISSING_VALUE != v and isinstance(v, base.Symbolic):
missing_child = v.sym_missing(flatten=False)
if missing_child:
missing[k] = missing_child
return missing
| (self) -> Dict[str, Any] | [
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|
40,884 | pyglove.core.symbolic.base | Inferential | Interface for values that could be dynamically inferred upon read.
Inferential values are objects whose values are not determined directly but
are instead derived from other sources, such as references (:class:`pg.Ref`)
to other objects or computed based on their context
(:class:`pg.symbolic.ValueFromParentChain`) such as the symbolic tree they
reside in.
When inferential values are utilized as symbolic attributes, we can obtain
their original definition by invoking :meth:`pg.Symbolic.sym_getattr`, and
their inferred values can be retrieved by calling
:meth:`pg.Symbolic.sym_inferred`. The values retrieved from :class:`pg.Dict`,
:class:`pg.List` and :class:`pg.Object` through `__getitem__` or
`__getattribute__` are all inferred values.
| class Inferential(TopologyAware, pg_typing.CustomTyping):
"""Interface for values that could be dynamically inferred upon read.
Inferential values are objects whose values are not determined directly but
are instead derived from other sources, such as references (:class:`pg.Ref`)
to other objects or computed based on their context
(:class:`pg.symbolic.ValueFromParentChain`) such as the symbolic tree they
reside in.
When inferential values are utilized as symbolic attributes, we can obtain
their original definition by invoking :meth:`pg.Symbolic.sym_getattr`, and
their inferred values can be retrieved by calling
:meth:`pg.Symbolic.sym_inferred`. The values retrieved from :class:`pg.Dict`,
:class:`pg.List` and :class:`pg.Object` through `__getitem__` or
`__getattribute__` are all inferred values.
"""
@abc.abstractmethod
def infer(self, **kwargs) -> Any:
"""Returns the inferred value.
Args:
**kwargs: Optional keyword arguments for inference, which are usually
inferential subclass specific.
Returns:
Inferred value.
Raises:
AttributeError: If the value cannot be inferred.
"""
| () | [
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]
|
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