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| # Copyright 2024 The Flax 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. | ||
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| from typing import Any, TypeVar | ||
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| import jax | ||
| from flax import struct | ||
| from flax.core import meta | ||
| from flax.nnx.nnx import variables as variableslib | ||
| import typing as tp | ||
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| A = TypeVar('A') | ||
| B = TypeVar('B') | ||
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| ####################################################### | ||
| ### Variable type <-> Linen collection name mapping ### | ||
| ####################################################### | ||
| # Assumption: the mapping is 1-1 and unique. | ||
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| VariableTypeCache: dict[str, tp.Type[variableslib.Variable[tp.Any]]] = {} | ||
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| def variable_type(name: str) -> tp.Type[variableslib.Variable[tp.Any]]: | ||
| """Given a Linen-style collection name, get or create its corresponding NNX Variable type.""" | ||
| if name not in VariableTypeCache: | ||
| VariableTypeCache[name] = type(name, (variableslib.Variable,), {}) | ||
| return VariableTypeCache[name] | ||
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| def variable_type_name(typ: tp.Type[variableslib.Variable[tp.Any]]) -> str: | ||
| """Given an NNX Variable type, get or create its Linen-style collection name. | ||
| Should output the exact inversed result of `variable_type()`.""" | ||
| for name, t in VariableTypeCache.items(): | ||
| if typ == t: | ||
| return name | ||
| name = typ.__name__ | ||
| if name in VariableTypeCache: | ||
| raise ValueError( | ||
| 'Name {name} is already registered in the registry as {VariableTypeCache[name]}. ' | ||
| 'It cannot be linked with this type {typ}.' | ||
| ) | ||
| register_variable_name_type_pair(name, typ) | ||
| return name | ||
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| def register_variable_name_type_pair(name, typ, overwrite = False): | ||
| """Register a pair of variable type name (like Linen collections) and its NNX type.""" | ||
| if not overwrite and name in VariableTypeCache: | ||
| raise ValueError(f'Name {name} already mapped to type {VariableTypeCache[name]}. ' | ||
| 'To overwrite, call with `overwrite=True`.') | ||
| VariableTypeCache[name] = typ | ||
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| # add known variable type names | ||
| register_variable_name_type_pair('params', variableslib.Param) | ||
| register_variable_name_type_pair('batch_stats', variableslib.BatchStat) | ||
| register_variable_name_type_pair('cache', variableslib.Cache) | ||
| register_variable_name_type_pair('intermediates', variableslib.Intermediate) | ||
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| def sort_variable_types(types: tp.Iterable[type]): | ||
| def _variable_parents_count(t: type): | ||
| return sum(1 for p in t.mro() if issubclass(p, variableslib.Variable)) | ||
| parent_count = {t: _variable_parents_count(t) for t in types} | ||
| return sorted(types, key=lambda t: -parent_count[t]) | ||
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| ############################################# | ||
| ### NNX Variable <-> Linen metadata boxes ### | ||
| ############################################# | ||
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| class NNXMeta(struct.PyTreeNode, meta.AxisMetadata[A]): | ||
| """Default Flax metadata class for `nnx.VariableState`. | ||
| """ | ||
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| var_type: type[variableslib.Variable[tp.Any]] = struct.field(pytree_node=False) | ||
| value: Any = struct.field(pytree_node=True) | ||
| metadata: dict[str, tp.Any] = struct.field(pytree_node=False) | ||
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| def unbox(self) -> A: | ||
| return self.value | ||
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| def replace_boxed(self, val: B) -> 'NNXMeta[B]': | ||
| return self.replace(value=val) # type: ignore | ||
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| def add_axis(self, index: int, params: dict[Any, Any]) -> 'NNXMeta[A]': | ||
| # TODO: implement this, supporting hooks | ||
| return self | ||
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| def remove_axis(self, index: int, params: dict[Any, Any]) -> 'NNXMeta[A]': | ||
| # TODO: implement this, supporting hooks | ||
| return self | ||
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| def to_linen_var(vs: variableslib.VariableState) -> meta.AxisMetadata: | ||
| metadata = vs.get_metadata() | ||
| if 'linen_meta_type' in metadata: | ||
| if metadata['linen_meta_type'] is not meta.Partitioned: | ||
| raise ValueError('Not supporting Linen metadata types other than nn.Partitioned') | ||
| return meta.Partitioned(vs.value, names=metadata['sharding'], mesh=metadata['mesh']) | ||
| return NNXMeta(vs.type, vs.value, vs.get_metadata()) | ||
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| def get_col_name(keypath: tp.Sequence[Any]) -> str: | ||
| """Given the keypath of a Flax variable type, return its Linen collection name.""" | ||
| # Infer variable type from the leaf's path, which contains its Linen collection name | ||
| assert isinstance(keypath[0], jax.tree_util.DictKey) | ||
| return str(keypath[0].key) | ||
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| def to_nnx_var(col: str, x: meta.AxisMetadata | Any) -> variableslib.Variable: | ||
| """Convert a Linen variable to an NNX variable. | ||
| This process needs the collection name, | ||
| """ | ||
| vtype = variable_type(col) | ||
| if isinstance(x, NNXMeta): | ||
| assert vtype == x.var_type, f'Type stored in NNXMeta {x.var_type} != type inferred from collection name {vtype}' | ||
| return x.var_type(x.value, **x.metadata) | ||
| if isinstance(x, meta.AxisMetadata): | ||
| if isinstance(x, meta.Partitioned): | ||
| return vtype(x.value, sharding=x.names, mesh=x.mesh, linen_meta_type=meta.Partitioned) | ||
| raise ValueError('Not yet supporting metadata types other than nn.Partitioned and NNXMeta') | ||
| return vtype(x) |
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