147 lines
3.9 KiB
Python
147 lines
3.9 KiB
Python
# Copyright 2025 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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"""Pallas helper functions."""
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from collections.abc import Callable
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import jax
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import jax.numpy as jnp
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from jax._src import core as jax_core
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from jax._src import checkify
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from jax._src import config
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from jax._src.pallas import core as pl_core
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from jax._src.pallas import utils as pl_utils
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from jax._src.pallas import pallas_call
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@jax.named_call
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def empty(
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shape: tuple[int, ...],
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dtype: jax.typing.DTypeLike,
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*,
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memory_space: object | None = None,
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interpret: bool = False,
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backend: pl_core.Backend | None = None,
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):
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return empty_like(
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jax.ShapeDtypeStruct(shape, dtype),
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memory_space=memory_space,
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interpret=interpret,
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backend=backend,
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)
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@jax.named_call
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def empty_like(
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x: object,
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*,
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memory_space: object | None = None,
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interpret: bool = False,
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backend: pl_core.Backend | None = None,
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):
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if hasattr(x, 'memory_space'):
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if memory_space is not None:
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raise ValueError(
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'memory_space cannot be specified for a MemoryRef object.'
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)
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memory_space = x.memory_space
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if memory_space is None:
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memory_space = pl_core.MemorySpace.ANY
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return pallas_call.pallas_call(
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# No-op to leave the out_ref uninitialized
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lambda *_: None,
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out_specs=jax.tree.map(
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lambda _: pl_core.BlockSpec(memory_space=memory_space), x
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),
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out_shape=x,
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interpret=interpret,
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backend=backend,
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)()
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def empty_ref_like(
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x: object, *, backend: pl_core.Backend | None = None
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) -> jax.Array:
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"""Returns an empty array Ref with same shape/dtype/memory space as x."""
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match x:
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case pl_core.MemoryRef():
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memory_space = x.memory_space
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case jax.ShapeDtypeStruct():
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memory_space = pl_core.MemorySpace.ANY
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case _:
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raise ValueError(f'alloc_ref does not support {type(x)}')
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out = empty_like(x, backend=backend)
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return jax_core.mutable_array(out, memory_space=memory_space)
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def when(condition):
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def _wrapped(f):
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if isinstance(condition, bool):
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if condition:
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f()
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else:
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jax.lax.cond(condition, f, lambda: None)
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return _wrapped
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def loop(
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lower: jax.typing.ArrayLike,
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upper: jax.typing.ArrayLike,
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*,
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step: jax.typing.ArrayLike = 1,
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unroll: int | bool | None = None,
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) -> Callable[[Callable[[jax.Array], None]], None]:
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"""Returns a decorator that calls the decorated function in a loop."""
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idx_type = jnp.result_type(lower, upper, step)
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lower = jax.lax.convert_element_type(lower, idx_type)
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upper = jax.lax.convert_element_type(upper, idx_type)
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step = jax.lax.convert_element_type(step, idx_type)
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def decorator(body):
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jax.lax.fori_loop(
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0,
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pl_utils.cdiv(upper - lower, step),
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lambda idx, _: body(lower + idx * step),
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init_val=None,
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unroll=unroll,
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)
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return decorator
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_ENABLE_DEBUG_CHECKS = config.bool_state(
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"jax_pallas_enable_debug_checks",
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default=False,
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help=(
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"If set, ``pl.debug_check`` calls are checked at runtime. Otherwise,"
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" they are a noop."
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),
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)
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enable_debug_checks = _ENABLE_DEBUG_CHECKS
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def debug_checks_enabled() -> bool:
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"""Returns runtime checks are enabled."""
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return _ENABLE_DEBUG_CHECKS.value
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def debug_check(condition, message):
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"""Check the condition if
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:func:`~jax.experimental.pallas.enable_debug_checks` is set, otherwise
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do nothing.
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"""
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return checkify.debug_check(condition, message)
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