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// tree/build-tree.h
// Copyright 2009-2011 Microsoft Corporation
// See ../../COPYING for clarification regarding multiple authors
//
// Licensed 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
//
// THIS CODE IS PROVIDED *AS IS* BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
// KIND, EITHER EXPRESS OR IMPLIED, INCLUDING WITHOUT LIMITATION ANY IMPLIED
// WARRANTIES OR CONDITIONS OF TITLE, FITNESS FOR A PARTICULAR PURPOSE,
// MERCHANTABLITY OR NON-INFRINGEMENT.
// See the Apache 2 License for the specific language governing permissions and
// limitations under the License.
#ifndef KALDI_TREE_BUILD_TREE_H_
#define KALDI_TREE_BUILD_TREE_H_
// The file build-tree.h contains outer-level routines used in tree-building
// and related tasks, that are directly called by the command-line tools.
#include "tree/build-tree-utils.h"
#include "tree/context-dep.h"
namespace kaldi {
/// \defgroup tree_group_top Top-level tree-building functions
/// See \ref tree_internals for context.
/// \ingroup tree_group
/// @{
// Note, in tree_group_top we also include AccumulateTreeStats, in
// ../hmm/tree-accu.h (it has some extra dependencies so we didn't
// want to include it here).
/**
* BuildTree is the normal way to build a set of decision trees.
* The sets "phone_sets" dictate how we set up the roots of the decision trees.
* each set of phones phone_sets[i] has shared decision-tree roots, and if
* the corresponding variable share_roots[i] is true, the root will be shared
* for the different HMM-positions in the phone. All phones in "phone_sets"
* should be in the stats (use FixUnseenPhones to ensure this).
* if for any i, do_split[i] is false, we will not do any tree splitting for
* phones in that set.
* @param qopts [in] Questions options class, contains questions for each key
* (e.g. each phone position)
* @param phone_sets [in] Each element of phone_sets is a set of phones whose
* roots are shared together (prior to decision-tree splitting).
* @param phone2num_pdf_classes [in] A map from phones to the number of
* \ref pdf_class "pdf-classes"
* in the phone (this info is derived from the HmmTopology object)
* @param share_roots [in] A vector the same size as phone_sets; says for each
* phone set whether the root should be shared among all the
* pdf-classes or not.
* @param do_split [in] A vector the same size as phone_sets; says for each
* phone set whether decision-tree splitting should be done
* (generally true for non-silence phones).
* @param stats [in] The statistics used in tree-building.
* @param thresh [in] Threshold used in decision-tree splitting (e.g. 1000),
* or you may use 0 in which case max_leaves becomes the
* constraint.
* @param max_leaves [in] Maximum number of leaves it will create; set this
* to a large number if you want to just specify "thresh".
* @param cluster_thresh [in] Threshold for clustering leaves after decision-tree
* splitting (only within each phone-set); leaves will be combined
* if log-likelihood change is less than this. A value about equal
* to "thresh" is suitable
* if thresh != 0; otherwise, zero will mean no clustering is done,
* or a negative value (e.g. -1) sets it to the smallest likelihood
* change seen during the splitting algorithm; this typically causes
* about a 20% reduction in the number of leaves.
* @param P [in] The central position of the phone context window, e.g. 1 for a
* triphone system.
* @return Returns a pointer to an EventMap object that is the tree.
*/
EventMap *BuildTree(Questions &qopts,
const std::vector<std::vector<int32> > &phone_sets,
const std::vector<int32> &phone2num_pdf_classes,
const std::vector<bool> &share_roots,
const std::vector<bool> &do_split,
const BuildTreeStatsType &stats,
BaseFloat thresh,
int32 max_leaves,
BaseFloat cluster_thresh, // typically == thresh. If negative, use smallest split.
int32 P);
/**
*
* BuildTreeTwoLevel builds a two-level tree, useful for example in building tied mixture
* systems with multiple codebooks. It first builds a small tree by splitting to
* "max_leaves_first". It then splits at the leaves of "max_leaves_first" (think of this
* as creating multiple little trees at the leaves of the first tree), until the total
* number of leaves reaches "max_leaves_second". It then outputs the second tree, along
* with a mapping from the leaf-ids of the second tree to the leaf-ids of the first tree.
* Note that the interface is similar to BuildTree, and in fact it calls BuildTree
* internally.
*
* The sets "phone_sets" dictate how we set up the roots of the decision trees.
* each set of phones phone_sets[i] has shared decision-tree roots, and if
* the corresponding variable share_roots[i] is true, the root will be shared
* for the different HMM-positions in the phone. All phones in "phone_sets"
* should be in the stats (use FixUnseenPhones to ensure this).
* if for any i, do_split[i] is false, we will not do any tree splitting for
* phones in that set.
*
* @param qopts [in] Questions options class, contains questions for each key
* (e.g. each phone position)
* @param phone_sets [in] Each element of phone_sets is a set of phones whose
* roots are shared together (prior to decision-tree splitting).
* @param phone2num_pdf_classes [in] A map from phones to the number of
* \ref pdf_class "pdf-classes"
* in the phone (this info is derived from the HmmTopology object)
* @param share_roots [in] A vector the same size as phone_sets; says for each
* phone set whether the root should be shared among all the
* pdf-classes or not.
* @param do_split [in] A vector the same size as phone_sets; says for each
* phone set whether decision-tree splitting should be done
* (generally true for non-silence phones).
* @param stats [in] The statistics used in tree-building.
* @param max_leaves_first [in] Maximum number of leaves it will create in first
* level of decision tree.
* @param max_leaves_second [in] Maximum number of leaves it will create in second
* level of decision tree. Must be > max_leaves_first.
* @param cluster_leaves [in] Boolean value; if true, we post-cluster the leaves produced
* in the second level of decision-tree split; if false, we don't.
* The threshold for post-clustering is the log-like change of the last
* decision-tree split; this typically causes about a 20% reduction in
* the number of leaves.
* @param P [in] The central position of the phone context window, e.g. 1 for a
* triphone system.
* @param leaf_map [out] Will be set to be a mapping from the leaves of the
* "big" tree to the leaves of the "little" tree, which you can
* view as cluster centers.
* @return Returns a pointer to an EventMap object that is the (big) tree.
*/
EventMap *BuildTreeTwoLevel(Questions &qopts,
const std::vector<std::vector<int32> > &phone_sets,
const std::vector<int32> &phone2num_pdf_classes,
const std::vector<bool> &share_roots,
const std::vector<bool> &do_split,
const BuildTreeStatsType &stats,
int32 max_leaves_first,
int32 max_leaves_second,
bool cluster_leaves,
int32 P,
std::vector<int32> *leaf_map);
/// GenRandStats generates random statistics of the form used by BuildTree.
/// It tries to do so in such a way that they mimic "real" stats. The event keys
/// and their corresponding values are:
/// - key == -1 == kPdfClass -> pdf-class, generally corresponds to
/// zero-based position in HMM (0, 1, 2 .. hmm_lengths[phone]-1)
/// - key == 0 -> phone-id of left-most context phone.
/// - key == 1 -> phone-id of one-from-left-most context phone.
/// - key == P-1 -> phone-id of central phone.
/// - key == N-1 -> phone-id of right-most context phone.
/// GenRandStats is useful only for testing but it serves to document the format of
/// stats used by BuildTreeDefault.
/// if is_ctx_dep[phone] is set to false, GenRandStats will not define the keys for
/// other than the P-1'th phone.
/// @param dim [in] dimension of features.
/// @param num_stats [in] approximate number of separate phones-in-context wanted.
/// @param N [in] context-size (typically 3)
/// @param P [in] central-phone position in zero-based numbering (typically 1)
/// @param phone_ids [in] integer ids of phones
/// @param hmm_lengths [in] lengths of hmm for phone, indexed by phone.
/// @param is_ctx_dep [in] boolean array indexed by phone, saying whether each phone
/// is context dependent.
/// @param ensure_all_phones_covered [in] Boolean argument: if true, GenRandStats
/// ensures that every phone is seen at least once in the central position (P).
/// @param stats_out [out] The statistics that this routine outputs.
void GenRandStats(int32 dim, int32 num_stats, int32 N, int32 P,
const std::vector<int32> &phone_ids,
const std::vector<int32> &hmm_lengths,
const std::vector<bool> &is_ctx_dep,
bool ensure_all_phones_covered,
BuildTreeStatsType *stats_out);
/// included here because it's used in some tree-building
/// calling code. Reads an OpenFst symbl table,
/// discards the symbols and outputs the integers
void ReadSymbolTableAsIntegers(std::string filename,
bool include_eps,
std::vector<int32> *syms);
/**
* Outputs sets of phones that are reasonable for questions
* to ask in the tree-building algorithm. These are obtained by tree
* clustering of the phones; for each node in the tree, all the leaves
* accessible from that node form one of the sets of phones.
* @param stats [in] The statistics as used for normal tree-building.
* @param phone_sets_in [in] All the phones, pre-partitioned into sets.
* The output sets will be various unions of these sets. These sets
* will normally correspond to "real phones", in cases where the phones
* have stress and position markings.
* @param all_pdf_classes_in [in] All the \ref pdf_class "pdf-classes"
* that we consider for clustering. In the normal case this is the singleton
* set {1}, which means that we only consider the central hmm-position
* of the standard 3-state HMM, for clustering purposes.
* @param P [in] The central position in the phone context window; normally
* 1 for triphone system.s
* @param questions_out [out] The questions (sets of phones) are output to here.
**/
void AutomaticallyObtainQuestions(BuildTreeStatsType &stats,
const std::vector<std::vector<int32> > &phone_sets_in,
const std::vector<int32> &all_pdf_classes_in,
int32 P,
std::vector<std::vector<int32> > *questions_out);
/// This function clusters the phones (or some initially specified sets of phones)
/// into sets of phones, using a k-means algorithm. Useful, for example, in building
/// simple models for purposes of adaptation.
void KMeansClusterPhones(BuildTreeStatsType &stats,
const std::vector<std::vector<int32> > &phone_sets_in,
const std::vector<int32> &all_pdf_classes_in,
int32 P,
int32 num_classes,
std::vector<std::vector<int32> > *sets_out);
/// Reads the roots file (throws on error). Format is lines like:
/// "shared split 1 2 3 4",
/// "not-shared not-split 5",
/// and so on. The numbers are indexes of phones.
void ReadRootsFile(std::istream &is,
std::vector<std::vector<int32> > *phone_sets,
std::vector<bool> *is_shared_root,
std::vector<bool> *is_split_root);
/// @}
}// end namespace kaldi
#endif
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