[nnx] add FlatState #4410
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[nnx] add FlatState #4410
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cgarciae
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flax/nnx/graph.py
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| def init(self, node: Node, items: tuple[tuple[Key, Leaf], ...]): | ||
| for key, value in items: | ||
| self.set_key(node, key, value) | ||
| # def init(self, node: Node, items: tp.Iterable[tuple[Key, Leaf]]): |
flax/nnx/graph.py
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| @@ -202,8 +205,8 @@ def get_node_impl_for_type(x: type[Node]) -> NodeImpl[Node, tp.Any, tp.Any]: | |||
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| class HashableMapping(tp.Mapping[HA, HB], tp.Hashable): | |||
| def __init__(self, mapping: tp.Mapping[HA, HB] | tp.Iterable[tuple[HA, HB]]): | |||
| self._mapping = dict(mapping) | |||
| def __init__(self, mapping: tp.Mapping[HA, HB], no_copy: bool = False): | |||
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Should this be copy=True instead? no_copy=False is double negation.
flax/nnx/graph.py
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| @@ -1787,7 +1794,7 @@ def is_pytree_node(x: tp.Any) -> bool: | |||
| elif isinstance(x, Variable): | |||
| return False | |||
| # knon pytree types | |||
| @@ -1787,7 +1794,7 @@ def is_pytree_node(x: tp.Any) -> bool: | |||
| elif isinstance(x, Variable): | |||
| return False | |||
| # knon pytree types | |||
| elif isinstance(x, (VariableState, State)): | |||
| elif type(x) is VariableState or type(x) is State: | |||
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This is not just a performance optimization, right? You no longer allow subclasses of VariableState or State.
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Correct. These should be treated more like Rust enums.
flax/nnx/statelib.py
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| flat_state[path] = f(path, variable_state) | ||
| return State.from_flat_path(flat_state) | ||
| result = [] | ||
| for path, variable_state in flat_state: |
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Nit: this can be a list comprehension.
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indeed, updated it to a list comprehension
flax/nnx/traversals.py
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| keys and returns True if the nested mapping is a leaf (i.e., should not be | ||
| flattened further). | ||
| sep: if specified, then the keys of the returned mapping will be | ||
| ``sep``-joined strings (if ``None``, then keys will be tuples). |
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Nit: blank line before "Returns".
flax/nnx/traversals.py
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| is_leaf: an optional function that takes the next nested mapping and nested | ||
| keys and returns True if the nested mapping is a leaf (i.e., should not be | ||
| flattened further). | ||
| sep: if specified, then the keys of the returned mapping will be |
flax/nnx/traversals.py
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| xs: Mapping[Any, Any], | ||
| /, | ||
| *, | ||
| is_leaf: None | IsLeafCallable = None, |
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What does this PR do?
FlatState[V]which is aSequence[tuple[PathParts, V]]that implements a trivial / low overhead pytree definition. The idea for subsequent optimization PRs is to haveto_treeandfrom_treeprimarily useFlatStateinstead ofStateto speed up training loops.graph.py.