NicolaLancellotti commented on a change in pull request #8795: URL: https://github.com/apache/tvm/pull/8795#discussion_r696745633
########## File path: src/relay/op/contrib/ethosu/convolution.cc ########## @@ -0,0 +1,212 @@ +/* + * 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. + */ + +/*! + * \file src/relay/op/contrib/ethosu/convolution.cc + * \brief Property def of the Arm(R) Ethos(TM)-U NPU convolution ops. + */ +#include "../../nn/convolution.h" + +#include <tvm/relay/base.h> +#include <tvm/relay/op.h> +#include <tvm/relay/qnn/attrs.h> +#include <tvm/tir/analysis.h> +#include <tvm/tir/data_layout.h> + +#include "../../../qnn/utils.h" +#include "common.h" + +namespace tvm { +namespace relay { +namespace op { +namespace contrib { +namespace ethosu { + +/*! \brief Attributes used by the Ethos(TM)-U NPU convolution operator */ +struct EthosuConv2DAttrs : public tvm::AttrsNode<EthosuConv2DAttrs> { + double ifm_scale; + int ifm_zero_point; + int weight_zero_point; + double ofm_scale; + int ofm_zero_point; + Array<IndexExpr> kernel_shape; + IndexExpr ofm_channels; + Array<IndexExpr> strides; + Array<IndexExpr> padding; + Array<IndexExpr> dilation; + String activation; + int clip_min; + int clip_max; + String upscale; + tvm::String ifm_layout; + tvm::String ofm_layout; + + TVM_DECLARE_ATTRS(EthosuConv2DAttrs, "relay.attrs.EthosuConv2DAttrs") { + TVM_ATTR_FIELD(ifm_scale).describe("The quantization scale for the Input Feature Map tensor."); + TVM_ATTR_FIELD(ifm_zero_point) + .describe("The quantization zero point for the Input Feature Map tensor."); + TVM_ATTR_FIELD(weight_zero_point) + .describe("The quantization zero point for the weight tensor."); + TVM_ATTR_FIELD(ofm_scale).describe("The quantization scale for the Output Feature Map tensor."); + TVM_ATTR_FIELD(ofm_zero_point) + .describe("The quantization zero point for the Output Feature Map tensor."); + TVM_ATTR_FIELD(kernel_shape) + .describe("The 2 dimensional kernel shape as (kernel_height, kernel_width).") + .set_default(NullValue<Array<IndexExpr> >()); + TVM_ATTR_FIELD(ofm_channels) + .describe("The number of OFM channels.") + .set_default(NullValue<IndexExpr>()); + TVM_ATTR_FIELD(strides) + .set_default(Array<IndexExpr>({1, 1})) + .describe("The 2 dimensional strides as (stride_height, stride_width)."); + TVM_ATTR_FIELD(padding) + .set_default(Array<IndexExpr>({0, 0, 0, 0})) + .describe("The 4 dimensional padding as (pad_top, pad_left, pad_bottom, pad_right)."); + TVM_ATTR_FIELD(dilation) + .set_default(Array<IndexExpr>({1, 1})) + .describe("The 2 dimensional dilation as (dilation_height, dilation_width)."); + TVM_ATTR_FIELD(activation) + .describe( + "The activation function to use. " + "'NONE' - no activation function. " + "'CLIP' - clip the output between clip_min and clip_max. " + "'TANH' - tanh activation function. " + "'SIGMOID' - sigmoid activation function. " + "'LUT' - use a look-up table to perform the activation function.") + .set_default("NONE"); + TVM_ATTR_FIELD(clip_min) + .describe("The minimum clipping value if activation = 'CLIP'.") + .set_default(0); + TVM_ATTR_FIELD(clip_max) + .describe("The maximum clipping value if activation = 'CLIP'.") + .set_default(0); + TVM_ATTR_FIELD(upscale) + .describe( + "The 2x2 upscaling mode to apply to the Input Feature Map tensor. " + "'NONE' - no upscaling. " + "'NEAREST' - upscale using nearest neighbour. " + "'ZEROS' - upscale using zeros.") + .set_default("NONE"); + TVM_ATTR_FIELD(ifm_layout) + .set_default("NHWC") + .describe("The layout of the Input Feature Map tensor. Can be 'NHWC' or 'NHCWB16'."); + TVM_ATTR_FIELD(ofm_layout) + .set_default("NHWC") + .describe("The layout of the Output Feature Map tensor. Can be 'NHWC' or 'NHCWB16'."); + } +}; + +TVM_REGISTER_NODE_TYPE(EthosuConv2DAttrs); + +bool EthosuConv2DRel(const Array<Type>& types, int num_inputs, const Attrs& attrs, + const TypeReporter& reporter) { + CHECK_EQ(types.size(), 5); + const auto* ifm = types[0].as<TensorTypeNode>(); + const auto* weight = types[1].as<TensorTypeNode>(); + const auto* scale_bias = types[2].as<TensorTypeNode>(); + if (ifm == nullptr || weight == nullptr) return false; + const auto* param = attrs.as<EthosuConv2DAttrs>(); + CHECK(param != nullptr) << "EthosuConv2DAttrs cannot be nullptr."; + CHECK(ifm->dtype == DataType::UInt(8) || ifm->dtype == DataType::Int(8)) + << "Expected ethosu_conv2d type(uint8) or type(int8) for ifm but was " << ifm->dtype; + CHECK(weight->dtype == DataType::UInt(8) || weight->dtype == DataType::Int(8)) + << "Expected ethosu_conv2d type(uint8) or type(int8) for weight but was " << weight->dtype; + CHECK(scale_bias->dtype == DataType::UInt(8)) + << "Expected ethosu_conv2d type(uint8) for scale_bias but was " << scale_bias->dtype; + + // The scale_bias should be provided as a tensor of size {ofm_channels, 10} + reporter->Assign(types[2], TensorType({weight->shape[0], 10}, DataType::UInt(8))); + + // Assign weight type {ofm_channels, kernel_height, kernel_width, ifm_channels} + reporter->Assign(types[1], TensorType({param->ofm_channels, param->kernel_shape[0], + param->kernel_shape[1], weight->shape[3]}, + weight->dtype)); + + // Assign ofm type + auto ofm_shape = + EthosuInferKernelOutput(ifm->shape, param->ifm_layout, param->ofm_layout, param->kernel_shape, + param->ofm_channels, param->dilation, param->strides, param->padding); + reporter->Assign(types[4], TensorType(ofm_shape, ifm->dtype)); + return true; +} + +Expr MakeEthosuConv2D(Expr ifm, Expr weight, Expr scale_bias, Expr lut, double ifm_scale, + int ifm_zero_point, int weight_zero_point, double ofm_scale, + int ofm_zero_point, Array<IndexExpr> kernel_shape, IndexExpr ofm_channels, + Array<IndexExpr> strides, Array<IndexExpr> padding, Array<IndexExpr> dilation, + String activation, int clip_min, int clip_max, String upscale, + String ifm_layout, String ofm_layout) { + auto attrs = make_object<EthosuConv2DAttrs>(); + attrs->ifm_scale = ifm_scale; + attrs->ifm_zero_point = ifm_zero_point; + attrs->weight_zero_point = weight_zero_point; + attrs->ofm_scale = ofm_scale; + attrs->ofm_zero_point = ofm_zero_point; + attrs->kernel_shape = std::move(kernel_shape); + attrs->ofm_channels = std::move(ofm_channels); + attrs->strides = std::move(strides); + attrs->padding = std::move(padding); + attrs->dilation = std::move(dilation); + attrs->activation = std::move(activation); + attrs->clip_min = clip_min; + attrs->clip_max = clip_max; + attrs->upscale = std::move(upscale); + attrs->ifm_layout = std::move(ifm_layout); + attrs->ofm_layout = std::move(ofm_layout); + static const Op& op = Op::Get("contrib.ethosu.conv2d"); + return Call(op, {ifm, weight, scale_bias, lut}, Attrs(attrs), {}); +} + +TVM_REGISTER_GLOBAL("relay.op._make.ethosu_conv2d").set_body_typed(MakeEthosuConv2D); + +RELAY_REGISTER_OP("contrib.ethosu.conv2d") + .describe(R"code(Arm(R) Ethos(TM)-U NPU 2D quantized convolution operator. + +This Relay operator corresponds to the hardware-implemented quantized +convolution operation found on Ethos(TM)-U NPUs. It accepts either NHWC +or NHCWB16 format for the input data (input feature map, or IFM) and Review comment: ```suggestion or NHCWB16 format for the input data (Input Feature Map, or IFM) and ``` -- 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]
