Initial import: grid-bot — grid trading bot for BTC-USDT on Cifra Markets
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Kolp
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#if !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)
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/*
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* Copyright (c) Meta Platforms, Inc. and affiliates.
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* All rights reserved.
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*
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* This source code is licensed under the BSD-style license found in the
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* LICENSE file in the root directory of this source tree.
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*/
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#pragma once
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#include <array>
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#include <stdexcept>
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#include <string>
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#include <type_traits>
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namespace fbgemm {
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template <int N, int... Vals>
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constexpr std::enable_if_t<N == sizeof...(Vals), std::array<int, N>>
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array_of_ones() {
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return std::array<int, N>{{Vals...}};
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}
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template <int N, int... Vals>
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constexpr std::enable_if_t<N != sizeof...(Vals), std::array<int, N>>
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array_of_ones() {
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return array_of_ones<N, Vals..., 1>();
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}
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template <int N, int... Vals>
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constexpr std::enable_if_t<N == sizeof...(Vals), std::array<int, N>>
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array_of_zeroes() {
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return std::array<int, N>{{Vals...}};
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}
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template <int N, int... Vals>
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constexpr std::enable_if_t<N != sizeof...(Vals), std::array<int, N>>
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array_of_zeroes() {
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return array_of_zeroes<N, Vals..., 0>();
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}
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/**
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* @brief A struct to conveniently store all convolution parameters.
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*/
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template <int SPATIAL_DIM = 2>
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struct conv_param_t {
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int MB; ///< Mini Batch size
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int IC; ///< Number of Input Channels
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int OC; ///< Number of Output Channels
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std::array<int, SPATIAL_DIM> IN_DIM; ///< Input Image Dimension
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int G; ///< Number of Groups
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std::array<int, SPATIAL_DIM> K; ///< Filter (Kernel) dimensions
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std::array<int, SPATIAL_DIM> stride; //< Strides
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std::array<int, SPATIAL_DIM * 2>
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pad; //< Padding (first SPATIAL_DIM is for prev/top/left padding, second
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// SPATIAL_DIM is for next/bottom/right padding)
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std::array<int, SPATIAL_DIM> dilation; //< Kernel dilation
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// The following are derived parameters
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std::array<int, SPATIAL_DIM> OUT_DIM; //< Output Image Dimension
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std::array<int, SPATIAL_DIM> IN_DIMP; //< Input Image Dimension Padded
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// The following is for tranposed convolution
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std::array<int, SPATIAL_DIM>
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output_pad; //< Padding (next/bottom/right padding in output buffer)
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bool transposed;
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/**
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* @brief Constructor for initializing the convolution parameters.
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*/
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conv_param_t(
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int mb,
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int ic,
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int oc,
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std::array<int, SPATIAL_DIM> in_dim,
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int g,
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std::array<int, SPATIAL_DIM> k,
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std::array<int, SPATIAL_DIM> strd,
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std::array<int, SPATIAL_DIM * 2> pd,
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std::array<int, SPATIAL_DIM> dilations = array_of_ones<SPATIAL_DIM>(),
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std::array<int, SPATIAL_DIM> otpt_pd = array_of_zeroes<SPATIAL_DIM>(),
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bool transposed = false)
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: MB(mb),
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IC(ic),
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OC(oc),
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IN_DIM(in_dim),
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G(g),
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K(k),
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stride(strd),
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pad(pd),
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dilation(dilations),
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output_pad(otpt_pd),
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transposed(transposed) {
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if (ic % g != 0) {
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throw std::runtime_error(
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"groups = " + std::to_string(g) +
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" does not divide number of input channels = " + std::to_string(ic));
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}
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if (oc % g != 0) {
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throw std::runtime_error(
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"groups = " + std::to_string(g) +
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" does not divide number of output channels = " + std::to_string(oc));
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}
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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if (transposed) {
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this->IN_DIMP[d] = this->IN_DIM[d] +
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(this->dilation[d] * (this->K[d] - 1) - this->pad[d]) +
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(this->dilation[d] * (this->K[d] - 1) - this->pad[SPATIAL_DIM + d]);
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this->OUT_DIM[d] = (this->IN_DIM[d] - 1) * this->stride[d] -
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this->pad[d] - this->pad[SPATIAL_DIM + d] +
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this->dilation[d] * (this->K[d] - 1) + output_pad[d] + 1;
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} else {
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IN_DIMP[d] = IN_DIM[d] + pad[d] + pad[SPATIAL_DIM + d];
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OUT_DIM[d] =
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(IN_DIMP[d] - dilation[d] * (K[d] - 1) - 1) / stride[d] + 1;
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}
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}
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}
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/**
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* @brief Helper function to get convolution parameters as string.
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*/
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std::string toString() const {
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std::string dim_string[3] = {"T", "H", "W"};
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std::string out;
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out += "MB:" + std::to_string(MB) + ", ";
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out += "IC:" + std::to_string(IC) + ", ";
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out += "OC:" + std::to_string(OC) + ", ";
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if constexpr (SPATIAL_DIM <= 3) {
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "I" + dim_string[3 - SPATIAL_DIM + d] + ":" +
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std::to_string(IN_DIM[d]) + ", ";
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}
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} else {
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "I" + std::to_string(d) + ":" + std::to_string(IN_DIM[d]) + ", ";
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}
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}
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out += "G:" + std::to_string(G) + ", ";
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if constexpr (SPATIAL_DIM <= 3) {
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "K" + dim_string[3 - SPATIAL_DIM + d] + ":" +
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std::to_string(K[d]) + ", ";
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}
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "stride_" + dim_string[3 - SPATIAL_DIM + d] + ":" +
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std::to_string(stride[d]) + ", ";
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}
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for (int d = 0; d < SPATIAL_DIM * 2; ++d) {
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out += "pad_" + dim_string[3 - SPATIAL_DIM + (d % SPATIAL_DIM)] + ":" +
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std::to_string(pad[d]) + ", ";
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}
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "dilation_" + dim_string[3 - SPATIAL_DIM + d] + ":" +
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std::to_string(dilation[d]);
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if (d < SPATIAL_DIM - 1) {
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out += ", ";
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}
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}
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} else {
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "K" + std::to_string(d) + ":" + std::to_string(K[d]) + ", ";
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}
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "stride_" + std::to_string(d) + ":" + std::to_string(stride[d]) +
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", ";
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}
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "pad_" + std::to_string(d) + ":" + std::to_string(pad[d]);
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if (d < SPATIAL_DIM * 2 - 1) {
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out += ", ";
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}
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}
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "dilation_" + std::to_string(d) + ":" +
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std::to_string(dilation[d]) + ", ";
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}
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}
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if (transposed) {
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for (int d = 0; d < SPATIAL_DIM; ++d) {
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out += "output_padding_" + std::to_string(d) + ":" +
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std::to_string(output_pad[d]) + ", ";
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}
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}
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return out;
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}
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};
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} // namespace fbgemm
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#else
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#error "This file should not be included when either TORCH_STABLE_ONLY or TORCH_TARGET_VERSION is defined."
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#endif // !defined(TORCH_STABLE_ONLY) && !defined(TORCH_TARGET_VERSION)
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