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/*
* Copyright (c) Facebook, Inc. and its affiliates.
* All rights reserved.
* This source code is licensed under the BSD-style license found in the
* LICENSE file in the root directory of this source tree.
*/
#pragma once
#include <array>
#include <string>
namespace fbgemm {
/**
* @brief A struct to conveniently store all convolution parameters.
*/
template <int SPATIAL_DIM = 2>
struct conv_param_t {
int MB; ///< Mini Batch size
int IC; ///< Number of Input Channels
int OC; ///< Number of Output Channels
std::array<int, SPATIAL_DIM> IN_DIM; ///< Input Image Dimension
int G; ///< Number of Groups
std::array<int, SPATIAL_DIM> K; ///< Filter (Kernel) dimensions
std::array<int, SPATIAL_DIM> stride; //< Strides
std::array<int, SPATIAL_DIM * 2>
pad; //< Padding (first SPATIAL_DIM is for prev/top/left padding, second
// SPATIAL_DIM is for next/bottom/right padding)
std::array<int, SPATIAL_DIM> dilation; //< Kernel dilation
// The following are derived parameters
std::array<int, SPATIAL_DIM> OUT_DIM; //< Output Image Dimension
std::array<int, SPATIAL_DIM> IN_DIMP; //< Input Image Dimension Padded
/**
* @brief Constructor for initializing the convolution parameters.
* TODO: Dilation is not handled correctly.
*/
conv_param_t(
int mb,
int ic,
int oc,
std::array<int, SPATIAL_DIM> in_dim,
int g,
std::array<int, SPATIAL_DIM> k,
std::array<int, SPATIAL_DIM> strd,
std::array<int, SPATIAL_DIM * 2> pd,
std::array<int, SPATIAL_DIM> dilations = {})
: MB(mb),
IC(ic),
OC(oc),
IN_DIM(in_dim),
G(g),
K(k),
stride(strd),
pad(pd),
dilation(dilations) {
if (ic % g != 0) {
throw std::runtime_error(
"groups = " + std::to_string(g) +
" does not divide number of input channels = " + std::to_string(ic));
}
if (oc % g != 0) {
throw std::runtime_error(
"groups = " + std::to_string(g) +
" does not divide number of output channels = " + std::to_string(oc));
}
bool dilation_unset = true;
for (int d = 0; d < SPATIAL_DIM; ++d) {
if (dilation[d] != 0) {
dilation_unset = false;
break;
}
}
if (dilation_unset) {
dilation.fill(1);
}
for (int d = 0; d < SPATIAL_DIM; ++d) {
IN_DIMP[d] = IN_DIM[d] + pad[d] + pad[SPATIAL_DIM + d];
OUT_DIM[d] = (IN_DIMP[d] - dilation[d] * (K[d] - 1) - 1) / stride[d] + 1;
}
}
/**
* @brief Helper function to get convolution parameters as string.
*/
std::string toString() const {
std::string dim_string[3] = {"T", "H", "W"};
std::string out = "";
out += "MB:" + std::to_string(MB) + ", ";
out += "IC:" + std::to_string(IC) + ", ";
out += "OC:" + std::to_string(OC) + ", ";
if (SPATIAL_DIM <= 3) {
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "I" + dim_string[3 - SPATIAL_DIM + d] + ":" +
std::to_string(IN_DIM[d]) + ", ";
}
} else {
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "I" + std::to_string(d) + ":" + std::to_string(IN_DIM[d]) + ", ";
}
}
out += "G:" + std::to_string(G) + ", ";
if (SPATIAL_DIM <= 3) {
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "K" + dim_string[3 - SPATIAL_DIM + d] + ":" +
std::to_string(K[d]) + ", ";
}
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "stride_" + dim_string[3 - SPATIAL_DIM + d] + ":" +
std::to_string(stride[d]) + ", ";
}
for (int d = 0; d < SPATIAL_DIM * 2; ++d) {
out += "pad_" + dim_string[3 - SPATIAL_DIM + (d % SPATIAL_DIM)] + ":" +
std::to_string(pad[d]);
if (d < SPATIAL_DIM * 2 - 1) {
out += ", ";
}
}
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "dilation_" + dim_string[3 - SPATIAL_DIM + d] + ":" +
std::to_string(dilation[d]) + ", ";
}
} else {
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "K" + std::to_string(d) + ":" + std::to_string(K[d]) + ", ";
}
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "stride_" + std::to_string(d) + ":" + std::to_string(stride[d]) +
", ";
}
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "pad_" + std::to_string(d) + ":" + std::to_string(pad[d]);
if (d < SPATIAL_DIM * 2 - 1) {
out += ", ";
}
}
for (int d = 0; d < SPATIAL_DIM; ++d) {
out += "dilation_" + std::to_string(d) + ":" +
std::to_string(dilation[d]) + ", ";
}
}
return out;
}
};
} // namespace fbgemm
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