91 lines
4.2 KiB
Python
91 lines
4.2 KiB
Python
#################################################################################################
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#
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# Copyright (c) 2023 - 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: BSD-3-Clause
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#
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# Redistribution and use in source and binary forms, with or without
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# modification, are permitted provided that the following conditions are met:
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#
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# 1. Redistributions of source code must retain the above copyright notice, this
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# list of conditions and the following disclaimer.
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#
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# 2. Redistributions in binary form must reproduce the above copyright notice,
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# this list of conditions and the following disclaimer in the documentation
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# and/or other materials provided with the distribution.
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#
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# 3. Neither the name of the copyright holder nor the names of its
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# contributors may be used to endorse or promote products derived from
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# this software without specific prior written permission.
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#
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# THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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# AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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# IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
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# DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE
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# FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL
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# DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
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# SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER
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# CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY,
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# OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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#
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#################################################################################################
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"""
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Infer the underlying implement of each node.
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While the frontend only distinguish between Load/Store/Compute Node,
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each of these nodes can have different underlying implementation based
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on their layout. For instance, a LoadNode can be AuxLoad, Row/Col/Scalar broadcast, etc.
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This pass infers the underlying impl of each node
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"""
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import cutlass_cppgen.backend.evt.backend as evt_backend
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from cutlass_cppgen.backend.evt.ir import DAGIR, LoadNode
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from cutlass_cppgen.backend.evt.passes.pass_fix_element_d import PassFixElementD
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from cutlass_cppgen.backend.evt.passes.pass_manager import EVTPassBase
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from cutlass_cppgen.backend.evt.passes.pass_no_op_elimination import PassNoOpElimination
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from cutlass_cppgen.backend.evt.passes.pass_shape_type_propagation import PassShapeTypePropagation
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from cutlass_cppgen.backend.evt.passes.util import cc_map
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class PassGetImpl(EVTPassBase):
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"""
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While the frontend only distinguish between Load/Store/Compute Node,
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each of these nodes can have different underlying implementation based
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on their layout. For instance, a LoadNode can be AuxLoad, Row/Col/Scalar broadcast, etc.
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This pass infers the underlying impl of each node
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"""
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dependencies = [
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PassShapeTypePropagation, # The shape and type info are required for inference
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PassFixElementD
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]
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def __init__(self, dag_ir: DAGIR) -> None:
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super().__init__(dag_ir)
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self.no_op_elimination = PassNoOpElimination(dag_ir)
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def requires(self) -> None:
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# Verify "accum" is in the arg list
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if not self.dag_ir.has_node("accum"):
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raise SyntaxError("Cannot find 'accum' in the argument list.")
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def call(self):
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# The loop structure of the epilogue is determined by the
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# accumulator shape
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accumulator: LoadNode = self.dag_ir.get_node_meta("accum")
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problem_size = accumulator.tensor.shape
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for node_meta in self.dag_ir.node_metas_topological_order():
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node_meta.get_underlying_impl(problem_size)
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def ensures(self) -> None:
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# Some nodes will be lowered to NoOp, eliminate them
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self.no_op_elimination()
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# Lower to cc-specific impl
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for node_meta in self.dag_ir.nodes_meta:
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node_impl_ccs = getattr(evt_backend, f"sm{cc_map[self.cc]}_nodes")
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node_meta.underlying_impl = getattr(
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node_impl_ccs,
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f"Sm{cc_map[self.cc]}" + node_meta.underlying_impl.__class__.__name__
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)(node_meta)
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