NicolaLancellotti commented on a change in pull request #9442: URL: https://github.com/apache/tvm/pull/9442#discussion_r743008661
########## File path: python/tvm/relay/backend/contrib/ethosu/op/binary_elementwise.py ########## @@ -0,0 +1,206 @@ +# 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=unused-argument +"""Relay operators for binary elementwise operators for Arm(R) Ethos(TM)-U NPU""" +import tvm +from tvm.relay.op import _make +from tvm.topi.generic import schedule_injective +from tvm.relay.op.op import OpStrategy +from tvm.relay.op import strategy as _strategy + +from ..te import binary_elementwise_compute + + +def _extract_ethosu_binary_elementwise_params(attrs, args): + """Get the parameters necessary to construct a ethosu_binary_elementwise compute TE + from a ethosu_binary_elementwise Relay call.""" + ifm = args[0] + ifm2 = args[1] + lut = args[2] + operator_type = attrs.operator_type + ifm_scale = attrs.ifm_scale + ifm_zero_point = attrs.ifm_zero_point + ifm2_scale = attrs.ifm2_scale + ifm2_zero_point = attrs.ifm2_zero_point + ofm_scale = attrs.ofm_scale + ofm_zero_point = attrs.ofm_zero_point + ofm_channels = attrs.ofm_channels + reversed_operands = attrs.reversed_operands + activation = attrs.activation + clip_min = attrs.clip_min + clip_max = attrs.clip_max + ifm_layout = attrs.ifm_layout + ifm2_layout = attrs.ifm2_layout + ofm_layout = attrs.ofm_layout + + return ( + ifm, + ifm2, + lut, + operator_type, + ifm_scale, + ifm_zero_point, + ifm2_scale, + ifm2_zero_point, + ofm_scale, + ofm_zero_point, + ofm_channels, + reversed_operands, + activation, + clip_min, + clip_max, + ifm_layout, + ifm2_layout, + ofm_layout, + ) + + [email protected]_op_attr("contrib.ethosu.binary_elementwise", "FTVMCompute") +def create_ethosu_binary_elementwise_compute(attrs, args, out_type): + """Create an ethosu_binary_elementwise compute op.""" + params = _extract_ethosu_binary_elementwise_params(attrs, args) + op = binary_elementwise_compute(*params) + return [op] + + [email protected]_op_attr("contrib.ethosu.binary_elementwise", "FTVMStrategy") +def binary_elementwise_strategy_ethosu(attrs, inputs, out_type, target): + strategy = OpStrategy() + strategy.add_implementation( + create_ethosu_binary_elementwise_compute, + _strategy.wrap_topi_schedule(schedule_injective), + name="ethosu_binary_elementwise", + ) + return strategy + + +def ethosu_binary_elementwise( + ifm: tvm.relay.Expr, + ifm2: tvm.relay.Expr, + lut: tvm.relay.Expr, + operator_type: str, + ifm_scale: float, + ifm_zero_point: int, + ifm2_scale: float, + ifm2_zero_point: int, + ofm_scale: float, + ofm_zero_point: int, + ofm_channels: int, + reversed_operands: bool, + ofm_dtype: str, + activation: str = "NONE", + clip_min: int = 0, + clip_max: int = 0, + ifm_layout: str = "NHWC", + ifm2_layout: str = "NHWC", + ofm_layout: str = "NHWC", +) -> tvm.relay.Call: + """This is a quantized binary elementwise operation as supported by + the NPU. It accepts either NHWC or NHCWB16 format + for the input data. + + Parameters + ---------- + ifm : tvm.relay.Expr + The Input Feature Map tensor (IFM). + ifm2 : tvm.relay.Expr + The Input Feature Map tensor 2 (IFM2). + lut : tvm.relay.Expr + The look-up table of values to use if activation = "LUT". + operator_type: str + The type of the binary elementwise operator. + "ADD" + "SUB" + "MUL" + "MIN" + "MAX" + "SHR" + "SHL" + ifm_scale : float + The quantization scale for the Input Feature Map tensor. + ifm_zero_point : int + The quantization zero point for the Input Feature Map tensor. + ifm2_scale : float + The quantization scale for the Input Feature Map tensor 2. + ifm2_zero_point : int + The quantization zero point for the Input Feature Map tensor 2. + ofm_scale : float + The quantization scale for the Output Feature Map tensor. + ofm_zero_point : int + The quantization zero point for the Output Feature Map tensor. + ofm_channels : int + The number of the Output Feature Map channels. + reversed_operands : bool + Specific if IFM2 is the first operand and IFM is the second operand. 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: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
