manupa-arm commented on a change in pull request #8795: URL: https://github.com/apache/tvm/pull/8795#discussion_r695436408
########## File path: python/tvm/relay/backend/contrib/ethosu/legalize.py ########## @@ -0,0 +1,200 @@ +# 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-argument, import-outside-toplevel +""" A set of passes to legalize some of operations for the NPU""" +import numpy as np + +import tvm +from tvm import relay +from tvm.relay.dataflow_pattern import DFPatternCallback +from tvm.relay.dataflow_pattern import wildcard +from tvm.relay.dataflow_pattern import is_op +from tvm.relay.dataflow_pattern import rewrite +from tvm.relay.backend.contrib.ethosu import op as ethosu_ops +from tvm.relay.backend.contrib.ethosu.errors import UnsupportedLayout +from tvm.relay.backend.contrib.ethosu import vela_api +from tvm.relay.op.contrib import ethosu as ethosu_patterns + + +class SplitRewriter(DFPatternCallback): + """Convert split operations to bunch of strided_slice operations, + because codegen is going to be based on strided_slices that are + close to in/out boxes of Vela High-Level Command Stream (HLCS). + Moreover, Vela HLCS is a high-level description of the supported + hardware operator. + """ + + def __init__(self): + super().__init__(require_type=True) + self.split_in = wildcard() + self.pattern = is_op("split")(self.split_in) + + @staticmethod + def get_section_begin_coords(split): + """Currently, the split can take an array of indices or an integer + indicating the number of splits. This helper functions unifies + this by making it a array of section begins. + + Parameters + ---------- + split : relay.Expr + The relay expression for split operator + + Returns + ------- + section_begins : list + A list containing integers corresponding to section + begins + """ + indices_or_sections = split.attrs.indices_or_sections + input_shape = split.args[0].checked_type.shape + split_axis = split.attrs.axis + + if isinstance(indices_or_sections, tvm.ir.container.Array): + # 0 is the beginning of the first section. + return [0] + list(indices_or_sections) + split_axis_len = input_shape[split_axis].value + section_length = split_axis_len // indices_or_sections.value + section_begins = list(range(0, split_axis_len, section_length)) + return section_begins + + def callback(self, pre, post, node_map): + splits_types = dict() + split_input = post.args[0] + for idx, field_type in enumerate(post.checked_type.fields): + split = relay.TupleGetItem(post, idx) + splits_types[split] = field_type + + split_begins = list() + split_ends = list() + section_begins_in_split_axis = self.get_section_begin_coords(post) + for split_cord in section_begins_in_split_axis: + # first begin is [0, 0, ... , 0] + begin_shape = [0 for i in range(len(split_input.checked_type.shape))] + begin_shape[post.attrs.axis] = split_cord + split_begins.append(begin_shape) + + end_shape = list(split_input.checked_type.shape) + # Only the split axis coordinate changes + end_shape[post.attrs.axis] = split_cord + split_ends.append(end_shape) + + # Coordinates needs to be shifted left because beginning + # of the next section is the end of the previous + split_ends = split_ends[1:] + # Last section end is the shape of the tensor itself. + split_ends.append(list(split_input.checked_type.shape)) + + strided_slices = list() + for sb, se in zip(split_begins, split_ends): + strided_slices.append(relay.strided_slice(split_input, sb, se)) + + return relay.Tuple(strided_slices) + + +class EthosUConv2DRewriter(DFPatternCallback): + """Convert conv2d related composite functions to ethosu_conv2d operators""" Review comment: Done -- 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: commits-unsubscr...@tvm.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
