elvin-n commented on code in PR #13100: URL: https://github.com/apache/tvm/pull/13100#discussion_r999171251
########## python/tvm/topi/adreno/reduction.py: ########## @@ -0,0 +1,154 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you 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. +# pylint: disable=invalid-name,unused-variable,too-many-locals,len-as-condition +"""Schedule for reduce operators""" +import numpy +import tvm +from tvm import te +from .. import tag +from ..utils import get_const_tuple +from .injective import schedule_injective_from_existing +from .utils import get_div + + +def _schedule_reduce_adreno(op, sch, is_idx_reduce=False): + if is_idx_reduce: + real_output = op.output(0) + temp_idx_input = op.input_tensors[0].op.output(0) + temp_val_input = op.input_tensors[0].op.output(1) + else: + real_output = op.output(0) + shape = get_const_tuple(real_output.shape) + latest4 = shape[-1] == 4 + div4 = numpy.prod(shape) % 4 == 0 + + # Fuse and split the axis + if latest4: + fused_outer = sch[real_output].fuse( + *[sch[real_output].op.axis[i] for i in range(len(sch[real_output].op.axis) - 1)] + ) + else: + fused_outer = sch[real_output].fuse( + *[sch[real_output].op.axis[i] for i in range(len(sch[real_output].op.axis))] + ) + + ftc = numpy.prod(shape) + a = fused_outer + if latest4: + sch[real_output].vectorize(sch[real_output].op.axis[-1]) + elif div4 and not is_idx_reduce: + a, b = sch[real_output].split(fused_outer, factor=4) + sch[real_output].vectorize(b) + ftc = ftc / 4 + + num_thread = get_div(ftc, 128) + + bx, outer_in = sch[real_output].split(a, factor=num_thread) + + sch[real_output].bind(bx, te.thread_axis("blockIdx.x")) + sch[real_output].bind(outer_in, te.thread_axis("threadIdx.y")) + if is_idx_reduce: + sch[temp_idx_input].compute_at(sch[real_output], outer_in) + sch[temp_val_input].compute_at(sch[real_output], outer_in) + + +def _enable_auto_inline(sch): + def is_scheduled(stage): + # auto inline requires the attach type is AttachType.kGroupRoot + conds = [ + len(stage.relations) == 0, + stage.attach_type == 1, + stage.all_iter_vars == stage.leaf_iter_vars, + ] + if not all(conds): + return True + return False + + for s in sch.stages: + if not s.is_output and isinstance(s.op, tvm.te.ComputeOp): + if is_scheduled(s) or len(s.op.reduce_axis) != 0: + return False + return True + + +def schedule_reduce(outs): Review Comment: re-used -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
