wehub-resource-sync
161 lines
4.9 KiB
Python
161 lines
4.9 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://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,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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"""Analysis used in TensorIR scheduling"""
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import tvm_ffi
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from tvm.runtime import Object
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from tvm.tirx.buffer import Buffer
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from tvm.tirx.expr import Expr
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from tvm.tirx.function import IndexMap, PrimFunc
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from tvm.tirx.stmt import For
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from . import _ffi_api
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from .schedule import SBlockRV, Schedule
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def suggest_index_map(
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buffer: Buffer,
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indices: list[Expr],
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loops: list[For],
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predicate: Expr,
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) -> IndexMap | None:
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"""Provided the access pattern to a buffer, suggest one of the possible layout
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transformation to maximize the locality of the access pattern.
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Parameters
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----------
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buffer : Buffer
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The buffer to be transformed.
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indices : List[Expr]
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The access pattern to the buffer.
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loops : List[For]
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The loops above the buffer.
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predicate : Expr
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The predicate of the access.
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Returns
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-------
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index_map : Optional[IndexMap]
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The suggested index map. None if no transformation is suggested.
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"""
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return _ffi_api.SuggestIndexMap( # type: ignore # pylint: disable=no-member
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buffer,
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indices,
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loops,
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predicate,
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)
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@tvm_ffi.register_object("s_tir.schedule.TensorizeInfo")
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class TensorizeInfo(Object):
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"""Necessary information used for tensorization."""
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def get_tensorize_loop_mapping(
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sch: Schedule, block: SBlockRV, desc_func: PrimFunc, allow_padding: bool = False
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) -> TensorizeInfo | None:
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"""Establish a mapping between loops in a target block and an intrinsic description
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Parameters
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----------
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sch : Schedule
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The schedule to be tensorized
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block : SBlockRV
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The target block to match against
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desc_func : PrimFunc
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The prim func describing the computation to be tensorized
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allow_padding : bool
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Whether to allow padding the block iters to match the intrinsic description
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Returns
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-------
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tensorize_info : Optional[TensorizeInfo]
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TensorizeInfo structure if a valid mapping is found, None otherwise
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"""
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return _ffi_api.GetTensorizeLoopMapping(sch, block, desc_func, allow_padding) # type: ignore
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@tvm_ffi.register_object("s_tir.schedule.AutoTensorizeMappingInfo")
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class AutoTensorizeMappingInfo(Object):
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"""Necessary information used to perform transformations for tensorization."""
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def get_auto_tensorize_mapping_info(
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sch: Schedule, block: SBlockRV, desc_func: PrimFunc
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) -> AutoTensorizeMappingInfo | None:
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"""Get mapping info between a target block and an intrinsic description including layout
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transformations to apply.
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Parameters
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----------
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sch : Schedule
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The schedule to be tensorized
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block : SBlockRV
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The compute block for auto tensorization
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desc_func : PrimFunc
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The prim func describing the computation to be tensorized
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Returns
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-------
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auto_tensorize_mapping_info : Optional[AutoTensorizeMappingInfo]
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AutoTensorizeMappingInfo structure if potential mappings found, None otherwise.
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Note
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----
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Returning a valid AutoTensorizeMappingInfo doesn't guarantee the block can be tensorized.
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We will need to apply the suggested layout transformations and then match against the tensor
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intrinsics.
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"""
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return _ffi_api.GetAutoTensorizeMappingInfo(sch, block, desc_func) # type: ignore
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def has_block(sch: Schedule, block_name: str) -> bool:
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"""Query if the given block name exists in the module associated with the provided schedule.
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Parameters
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----------
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sch : Schedule
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The schedule
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block_name : str
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The name of the block to query
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Returns
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-------
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yes/no: bool
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True if the given block exists in the schedule.
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"""
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return _ffi_api.HasBlock(sch, block_name) # type: ignore
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def is_output_block(sch: Schedule, block: SBlockRV) -> bool:
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"""Check whether the given block is an output block
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Parameters
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----------
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sch : Schedule
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The schedule object of the block
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block : SBlockRV
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The blockRV to be checked
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Returns
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-------
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yes/no : bool
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True if the given block is an output block
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"""
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return _ffi_api.IsOutputBlock(sch, block) # type: ignore
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