Tomotopy

* An issue where calling `convert_to_lda` of `tomotopy.HDPModel` with `min_cf > 0`, `min_df > 0` or `rm_top > 0` causes a crash has been fixed.
* A new argument `from_pseudo_doc` is added to `tomotopy.Document.get_topics` and `tomotopy.Document.get_topic_dist`.
This argument is only valid for documents of `PTModel`, it enables to control a source for computing topic distribution.
* A default value for argument `p` of `tomotopy.PTModel` has been changed. The new default value is `k * 10`.
* Using documents generated by `make_doc` without calling `infer` doesn't cause a crash anymore, but just print warning messages.
* An issue where the internal C++ code isn't compiled at clang c++17 environment has been fixed.

* An issue where `tomotopy.LDAModel.set_word_prior()` causes a crash has been fixed.
* Now `tomotopy.LDAModel.perplexity` and `tomotopy.LDAModel.ll_per_word` return the accurate value when `TermWeight` is not `ONE`.
* `tomotopy.LDAModel.used_vocab_weighted_freq` was added, which returns term-weighted frequencies of words.
* Now `tomotopy.LDAModel.summary()` shows not only the entropy of words, but also the entropy of term-weighted words.

* Now `tomotopy.DMRModel` and `tomotopy.GDMRModel` support multiple values of metadata (see https://github.com/bab2min/tomotopy/blob/main/examples/dmr_multi_label.py )
* The performance of `tomotopy.GDMRModel` was improved.
* A `copy()` method has been added for all topic models to do a deep copy.
* An issue was fixed where words that are excluded from training (by `min_cf`, `min_df`) have incorrect topic id. Now all excluded words have `-1` as topic id.
* Now all exceptions and warnings that generated by `tomotopy` follow standard Python types.
* Compiler requirements have been raised to C++14.

* A critical bug of asymmetric alphas was fixed. Due to this bug, version 0.11.0 has been removed from releases.

* A new topic model `tomotopy.PTModel` for short texts was added into the package.
* An issue was fixed where `tomotopy.HDPModel.infer` causes a segmentation fault sometimes.
* A mismatch of numpy API version was fixed.
* Now asymmetric document-topic priors are supported.
* Serializing topic models to `bytes` in memory is supported.
* An argument `normalize` was added to `get_topic_dist()`, `get_topic_word_dist()` and `get_sub_topic_dist()` for controlling normalization of results.
* Now `tomotopy.DMRModel.lambdas` and `tomotopy.DMRModel.alpha` give correct values.
* Categorical metadata supports for `tomotopy.GDMRModel` were added (see https://github.com/bab2min/tomotopy/blob/main/examples/gdmr_both_categorical_and_numerical.py ).
* Python3.5 support was dropped.

* An issue was fixed where `tomotopy.CTModel.train` fails with large K.
* An issue was fixed where `tomotopy.utils.Corpus` loses their `uid` values.