79 lines
2.5 KiB
Python
79 lines
2.5 KiB
Python
# Copyright 2021 The JAX Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# https://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License
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"""A bounded functional stack implementation.
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Used as a helper for expressing recursive algorithms such as QDWH-eig for
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Eigendecomposition on TPU.
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"""
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from __future__ import annotations
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from typing import Any, Tuple
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import jax
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from jax import lax
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import jax.numpy as jnp
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class Stack:
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"""A bounded functional stack implementation. Elements may be pytrees."""
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def __init__(self, size, data):
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"""Private constructor."""
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self._size = size
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self._data = data
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def __repr__(self):
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return f"Stack({self._size}, {self._data})"
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@staticmethod
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def create(capacity: int, prototype: Any) -> Stack:
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"""Creates a stack with size `capacity` with elements like `prototype`.
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`prototype` can be any JAX pytree. This function looks only at its
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structure; the specific values are ignored.
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"""
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return Stack(
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jnp.array(0, jnp.int32),
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jax.tree_util.tree_map(
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lambda x: jnp.zeros((capacity,) + tuple(x.shape), x.dtype), prototype))
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def empty(self) -> Any:
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"""Returns true if the stack is empty."""
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return self._size == 0
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def push(self, elem: Any) -> Stack:
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"""Pushes `elem` onto the stack, returning the updated stack."""
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return Stack(
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self._size + 1,
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jax.tree_util.tree_map(
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lambda x, y: lax.dynamic_update_index_in_dim(x, y, self._size, 0),
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self._data, elem))
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def pop(self) -> Tuple[Any, Stack]:
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"""Pops from the stack, returning an (elem, updated stack) pair."""
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elem = jax.tree_util.tree_map(
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lambda x: lax.dynamic_index_in_dim(x, self._size - 1, 0, keepdims=False),
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self._data)
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return elem, Stack(self._size - 1, self._data)
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def flatten(self):
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leaves, treedef = jax.tree_util.tree_flatten(self._data)
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return ([self._size] + leaves), treedef
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@staticmethod
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def unflatten(treedef, leaves):
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return Stack(leaves[0], jax.tree_util.tree_unflatten(treedef, leaves[1:]))
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jax.tree_util.register_pytree_node(Stack, Stack.flatten, Stack.unflatten)
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