Commit Graph

176 Commits

Author SHA1 Message Date
Adriane Boyd
ea450d652c
Exclude strings from v3.2+ source vector checks (#9697)
Exclude strings from `Vector.to_bytes()` comparions for v3.2+ `Vectors`
that now include the string store so that the source vector comparison
is only comparing the vectors and not the strings.
2021-11-19 08:51:19 +01:00
Paul O'Leary McCann
f3981bd0c8
Clarify how to fill in init_tok2vec after pretraining (#9639)
* Clarify how to fill in init_tok2vec after pretraining

* Ignore init_tok2vec arg in pretraining

* Update docs, config setting

* Remove obsolete note about not filling init_tok2vec early

This seems to have also caught some lines that needed cleanup.
2021-11-18 15:38:30 +01:00
github-actions[bot]
67d8c8a081
Auto-format code with black (#9664)
Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
2021-11-12 10:00:03 +01:00
Paul O'Leary McCann
8aa2d32ca9 Update jsonlcorpus constructor types 2021-11-09 16:20:19 +09:00
Paul O'Leary McCann
71fb00ed95
Update spacy/training/corpus.py
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2021-11-08 10:02:29 +00:00
Paul O'Leary McCann
141f12b92e Make Jsonl Corpus reader optional again 2021-11-07 18:56:23 +09:00
Adriane Boyd
e6f91b6f27
Format (#9630) 2021-11-05 09:56:26 +01:00
Adriane Boyd
c053f158c5
Add support for floret vectors (#8909)
* Add support for fasttext-bloom hash-only vectors

Overview:

* Extend `Vectors` to have two modes: `default` and `ngram`
  * `default` is the default mode and equivalent to the current
    `Vectors`
  * `ngram` supports the hash-only ngram tables from `fasttext-bloom`
* Extend `spacy.StaticVectors.v2` to handle both modes with no changes
  for `default` vectors
* Extend `spacy init vectors` to support ngram tables

The `ngram` mode **only** supports vector tables produced by this
fork of fastText, which adds an option to represent all vectors using
only the ngram buckets table and which uses the exact same ngram
generation algorithm and hash function (`MurmurHash3_x64_128`).
`fasttext-bloom` produces an additional `.hashvec` table, which can be
loaded by `spacy init vectors --fasttext-bloom-vectors`.

https://github.com/adrianeboyd/fastText/tree/feature/bloom

Implementation details:

* `Vectors` now includes the `StringStore` as `Vectors.strings` so that
  the API can stay consistent for both `default` (which can look up from
  `str` or `int`) and `ngram` (which requires `str` to calculate the
  ngrams).

* In ngram mode `Vectors` uses a default `Vectors` object as a cache
  since the ngram vectors lookups are relatively expensive.

  * The default cache size is the same size as the provided ngram vector
    table.

  * Once the cache is full, no more entries are added. The user is
    responsible for managing the cache in cases where the initial
    documents are not representative of the texts.

  * The cache can be resized by setting `Vectors.ngram_cache_size` or
    cleared with `vectors._ngram_cache.clear()`.

* The API ends up a bit split between methods for `default` and for
  `ngram`, so functions that only make sense for `default` or `ngram`
  include warnings with custom messages suggesting alternatives where
  possible.

* `Vocab.vectors` becomes a property so that the string stores can be
  synced when assigning vectors to a vocab.

* `Vectors` serializes its own config settings as `vectors.cfg`.

* The `Vectors` serialization methods have added support for `exclude`
  so that the `Vocab` can exclude the `Vectors` strings while serializing.

Removed:

* The `minn` and `maxn` options and related code from
  `Vocab.get_vector`, which does not work in a meaningful way for default
  vector tables.

* The unused `GlobalRegistry` in `Vectors`.

* Refactor to use reduce_mean

Refactor to use reduce_mean and remove the ngram vectors cache.

* Rename to floret

* Rename to floret in error messages

* Use --vectors-mode in CLI, vector init

* Fix vectors mode in init

* Remove unused var

* Minor API and docstrings adjustments

* Rename `--vectors-mode` to `--mode` in `init vectors` CLI
* Rename `Vectors.get_floret_vectors` to `Vectors.get_batch` and support
  both modes.
* Minor updates to Vectors docstrings.

* Update API docs for Vectors and init vectors CLI

* Update types for StaticVectors
2021-10-27 14:08:31 +02:00
Adriane Boyd
a803af9dfa Merge remote-tracking branch 'upstream/master' into chore/update-develop-from-master-v3.2-1 2021-10-26 11:53:50 +02:00
Connor Brinton
657af5f91f
🏷 Add Mypy check to CI and ignore all existing Mypy errors (#9167)
* 🚨 Ignore all existing Mypy errors

* 🏗 Add Mypy check to CI

* Add types-mock and types-requests as dev requirements

* Add additional type ignore directives

* Add types packages to dev-only list in reqs test

* Add types-dataclasses for python 3.6

* Add ignore to pretrain

* 🏷 Improve type annotation on `run_command` helper

The `run_command` helper previously declared that it returned an
`Optional[subprocess.CompletedProcess]`, but it isn't actually possible
for the function to return `None`. These changes modify the type
annotation of the `run_command` helper and remove all now-unnecessary
`# type: ignore` directives.

* 🔧 Allow variable type redefinition in limited contexts

These changes modify how Mypy is configured to allow variables to have
their type automatically redefined under certain conditions. The Mypy
documentation contains the following example:

```python
def process(items: List[str]) -> None:
    # 'items' has type List[str]
    items = [item.split() for item in items]
    # 'items' now has type List[List[str]]
    ...
```

This configuration change is especially helpful in reducing the number
of `# type: ignore` directives needed to handle the common pattern of:
* Accepting a filepath as a string
* Overwriting the variable using `filepath = ensure_path(filepath)`

These changes enable redefinition and remove all `# type: ignore`
directives rendered redundant by this change.

* 🏷 Add type annotation to converters mapping

* 🚨 Fix Mypy error in convert CLI argument verification

* 🏷 Improve type annotation on `resolve_dot_names` helper

* 🏷 Add type annotations for `Vocab` attributes `strings` and `vectors`

* 🏷 Add type annotations for more `Vocab` attributes

* 🏷 Add loose type annotation for gold data compilation

* 🏷 Improve `_format_labels` type annotation

* 🏷 Fix `get_lang_class` type annotation

* 🏷 Loosen return type of `Language.evaluate`

* 🏷 Don't accept `Scorer` in `handle_scores_per_type`

* 🏷 Add `string_to_list` overloads

* 🏷 Fix non-Optional command-line options

* 🙈 Ignore redefinition of `wandb_logger` in `loggers.py`

*  Install `typing_extensions` in Python 3.8+

The `typing_extensions` package states that it should be used when
"writing code that must be compatible with multiple Python versions".
Since SpaCy needs to support multiple Python versions, it should be used
when newer `typing` module members are required. One example of this is
`Literal`, which is available starting with Python 3.8.

Previously SpaCy tried to import `Literal` from `typing`, falling back
to `typing_extensions` if the import failed. However, Mypy doesn't seem
to be able to understand what `Literal` means when the initial import
means. Therefore, these changes modify how `compat` imports `Literal` by
always importing it from `typing_extensions`.

These changes also modify how `typing_extensions` is installed, so that
it is a requirement for all Python versions, including those greater
than or equal to 3.8.

* 🏷 Improve type annotation for `Language.pipe`

These changes add a missing overload variant to the type signature of
`Language.pipe`. Additionally, the type signature is enhanced to allow
type checkers to differentiate between the two overload variants based
on the `as_tuple` parameter.

Fixes #8772

*  Don't install `typing-extensions` in Python 3.8+

After more detailed analysis of how to implement Python version-specific
type annotations using SpaCy, it has been determined that by branching
on a comparison against `sys.version_info` can be statically analyzed by
Mypy well enough to enable us to conditionally use
`typing_extensions.Literal`. This means that we no longer need to
install `typing_extensions` for Python versions greater than or equal to
3.8! 🎉

These changes revert previous changes installing `typing-extensions`
regardless of Python version and modify how we import the `Literal` type
to ensure that Mypy treats it properly.

* resolve mypy errors for Strict pydantic types

* refactor code to avoid missing return statement

* fix types of convert CLI command

* avoid list-set confustion in debug_data

* fix typo and formatting

* small fixes to avoid type ignores

* fix types in profile CLI command and make it more efficient

* type fixes in projects CLI

* put one ignore back

* type fixes for render

* fix render types - the sequel

* fix BaseDefault in language definitions

* fix type of noun_chunks iterator - yields tuple instead of span

* fix types in language-specific modules

* 🏷 Expand accepted inputs of `get_string_id`

`get_string_id` accepts either a string (in which case it returns its 
ID) or an ID (in which case it immediately returns the ID). These 
changes extend the type annotation of `get_string_id` to indicate that 
it can accept either strings or IDs.

* 🏷 Handle override types in `combine_score_weights`

The `combine_score_weights` function allows users to pass an `overrides` 
mapping to override data extracted from the `weights` argument. Since it 
allows `Optional` dictionary values, the return value may also include 
`Optional` dictionary values.

These changes update the type annotations for `combine_score_weights` to 
reflect this fact.

* 🏷 Fix tokenizer serialization method signatures in `DummyTokenizer`

* 🏷 Fix redefinition of `wandb_logger`

These changes fix the redefinition of `wandb_logger` by giving a 
separate name to each `WandbLogger` version. For 
backwards-compatibility, `spacy.train` still exports `wandb_logger_v3` 
as `wandb_logger` for now.

* more fixes for typing in language

* type fixes in model definitions

* 🏷 Annotate `_RandomWords.probs` as `NDArray`

* 🏷 Annotate `tok2vec` layers to help Mypy

* 🐛 Fix `_RandomWords.probs` type annotations for Python 3.6

Also remove an import that I forgot to move to the top of the module 😅

* more fixes for matchers and other pipeline components

* quick fix for entity linker

* fixing types for spancat, textcat, etc

* bugfix for tok2vec

* type annotations for scorer

* add runtime_checkable for Protocol

* type and import fixes in tests

* mypy fixes for training utilities

* few fixes in util

* fix import

* 🐵 Remove unused `# type: ignore` directives

* 🏷 Annotate `Language._components`

* 🏷 Annotate `spacy.pipeline.Pipe`

* add doc as property to span.pyi

* small fixes and cleanup

* explicit type annotations instead of via comment

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
Co-authored-by: svlandeg <svlandeg@github.com>
2021-10-14 15:21:40 +02:00
Adriane Boyd
d98d525bc8 Merge remote-tracking branch 'upstream/master' into chore/update-develop-from-master-v3.1-3 2021-10-14 09:41:46 +02:00
Lj Miranda
6425b9a1c4
Include JsonlCorpus from the imports (#9431) 2021-10-12 15:39:14 +02:00
Adriane Boyd
4192e71599
Sync vocab in vectors and components sourced in configs (#9335)
Since a component may reference anything in the vocab, share the full
vocab when loading source components and vectors (which will include
`strings` as of #8909).

When loading a source component from a config, save and restore the
vocab state after loading source pipelines, in particular to preserve
the original state without vectors, since `[initialize.vectors]
= null` skips rather than resets the vectors.

The vocab references are not synced for components loaded with
`Language.add_pipe(source=)` because the pipelines are already loaded
and not necessarily with the same vocab. A warning could be added in
`Language.create_pipe_from_source` that it may be necessary to save and
reload before training, but it's a rare enough case that this kind of
warning may be too noisy overall.
2021-10-04 12:19:02 +02:00
Elia Robyn Lake (Robyn Speer)
5b0b0ca809
Move WandB loggers into spacy-loggers (#9223)
* factor out the WandB logger into spacy-loggers

Signed-off-by: Elia Robyn Speer <gh@arborelia.net>

* depend on spacy-loggers so they are available

Signed-off-by: Elia Robyn Speer <gh@arborelia.net>

* remove docs of spacy.WandbLogger.v2 (moved to spacy-loggers)

Signed-off-by: Elia Robyn Speer <elia@explosion.ai>

* Version number suggestions from code review

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>

* update references to WandbLogger

Signed-off-by: Elia Robyn Speer <elia@explosion.ai>

* make order of deps more consistent

Signed-off-by: Elia Robyn Speer <elia@explosion.ai>

Co-authored-by: Elia Robyn Speer <elia@explosion.ai>
Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
2021-09-29 11:12:50 +02:00
Adriane Boyd
03f234b739 Merge remote-tracking branch 'upstream/master' into develop 2021-09-27 09:10:45 +02:00
github-actions[bot]
015d439eb6
Auto-format code with black (#9234)
Co-authored-by: explosion-bot <explosion-bot@users.noreply.github.com>
2021-09-20 08:49:19 +02:00
Jozef Harag
865cfbc903
feat: add spacy.WandbLogger.v3 with optional run_name and entity parameters (#9202)
* feat: add `spacy.WandbLogger.v3` with optional `run_name` and `entity` parameters

* update versioning in docs

Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
2021-09-16 12:26:41 +02:00
Paul O'Leary McCann
f803a84571
Fix inference of epoch_resume (#9084)
* Fix inference of epoch_resume

When an epoch_resume value is not specified individually, it can often
be inferred from the filename. The value inference code was there but
the value wasn't passed back to the training loop.

This also adds a specific error in the case where no epoch_resume value
is provided and it can't be inferred from the filename.

* Add new error

* Always use the epoch resume value if specified

Before this the value in the filename was used if found
2021-09-01 14:17:42 +09:00
Sofie Van Landeghem
4d39430b82
Document use-case of freezing tok2vec (#8992)
* update error msg

* add sentence to docs

* expand note on frozen components
2021-08-26 09:50:35 +02:00
Edward
944ad6b1d4
Add new parameter for saving every n epoch in pretraining (#8912)
* Add parameter for saving every n epoch

* Add new parameter in schemas

* Add new parameter in default_config

* Adjust schemas

* format code
2021-08-12 11:14:48 +02:00
themrmax
de076194c4
Make ConsoleLogger flush after each logging line (#8810)
This is necessary to avoid "logging blackouts" when running training on Kubernetes pods
2021-08-02 14:33:38 +02:00
explosion-bot
a58ab6ea22 Auto-format code with black 2021-07-23 08:04:09 +00:00
Adriane Boyd
0e4b96c97e
Update lexeme ranks for loaded vectors (#8640)
Update the ranks for any lexemes that have been added to the vocab
before the vectors are added to the model.
2021-07-19 18:25:54 +10:00
Ines Montani
483f3175cb Tidy up [ci skip] 2021-07-17 13:43:15 +10:00
Adriane Boyd
5fd0b5207e
Fix vectors check for sourced components (#8559)
* Fix vectors check for sourced components

Since vectors are not loaded when components are sourced, store a hash
for the vectors of each sourced component and compare it to the loaded
vectors after the vectors are loaded from the `[initialize]` block.

* Pop temporary info

* Remove stored hash in remove_pipe

* Add default for pop

* Add additional convert/debug/assemble CLI tests
2021-07-06 12:43:17 +02:00
explosion-bot
ee37288a1f Auto-format code with black 2021-07-02 07:48:26 +00:00
Adriane Boyd
86d01e9229 Tidy up with flake8: imports, comparisons, etc. 2021-06-28 12:08:15 +02:00
Adriane Boyd
5eeb25f043 Tidy up code 2021-06-28 12:08:15 +02:00
Adriane Boyd
30d4eb506a
Fix setting empty entities in Example.from_dict (#8426) 2021-06-18 10:41:50 +02:00
Matthew Honnibal
6f5e308d17
Support negative examples in partial NER annotations (#8106)
* Support a cfg field in transition system

* Make NER 'has gold' check use right alignment for span

* Pass 'negative_samples_key' property into NER transition system

* Add field for negative samples to NER transition system

* Check neg_key in NER has_gold

* Support negative examples in NER oracle

* Test for negative examples in NER

* Fix name of config variable in NER

* Remove vestiges of old-style partial annotation

* Remove obsolete tests

* Add comment noting lack of support for negative samples in parser

* Additions to "neg examples" PR (#8201)

* add custom error and test for deprecated format

* add test for unlearning an entity

* add break also for Begin's cost

* add negative_samples_key property on Parser

* rename

* extend docs & fix some older docs issues

* add subclass constructors, clean up tests, fix docs

* add flaky test with ValueError if gold parse was not found

* remove ValueError if n_gold == 0

* fix docstring

* Hack in environment variables to try out training

* Remove hack

* Remove NER hack, and support 'negative O' samples

* Fix O oracle

* Fix transition parser

* Remove 'not O' from oracle

* Fix NER oracle

* check for spans in both gold.ents and gold.spans and raise if so, to prevent memory access violation

* use set instead of list in consistency check

Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
2021-06-17 17:33:00 +10:00
Adriane Boyd
5646fcbe46 Merge remote-tracking branch 'upstream/develop' into chore/develop-into-master-v3.1 2021-06-15 15:05:17 +02:00
Adriane Boyd
480a3bf3be
Make JsonlReader path optional (#8396)
To avoid config errors during training when `[corpora.pretrain.path]` is
`None` with the default `spacy.JsonlCorpus.v1` reader, make the reader
path optional, similar to `spacy.Corpus.v1`.
2021-06-15 14:55:15 +02:00
Sofie Van Landeghem
3c58c0323f
fix docs (#8200) 2021-05-27 10:48:59 +02:00
Sofie Van Landeghem
290bd6ed39
ensure tolerance is properly passed on (#8158) 2021-05-27 18:10:28 +10:00
Adriane Boyd
95c0833656
Add training option to set annotations on update (#7767)
* Add training option to set annotations on update

Add a `[training]` option called `set_annotations_on_update` to specify
a list of components for which the predicted annotations should be set
on `example.predicted` immediately after that component has been
updated. The predicted annotations can be accessed by later components
in the pipeline during the processing of the batch in the same `update`
call.

* Rename to annotates / annotating_components

* Add test for `annotating_components` when training from config

* Add documentation
2021-04-26 16:53:53 +02:00
Adriane Boyd
bdb485cc80
Add callback to copy vocab/tokenizer from model (#7750)
* Add callback to copy vocab/tokenizer from model

Add callback `spacy.copy_from_base_model.v1` to copy the tokenizer
settings and/or vocab (including vectors) from a base model.

* Move spacy.copy_from_base_model.v1 to spacy.training.callbacks

* Add documentation

* Modify to specify model as tokenizer and vocab params
2021-04-22 12:36:50 +02:00
Adriane Boyd
f68fc29130
Update sent_starts in Example.from_dict (#7847)
* Update sent_starts in Example.from_dict

Update `sent_starts` for `Example.from_dict` so that `Optional[bool]`
values have the same meaning as for `Token.is_sent_start`.

Use `Optional[bool]` as the type for sent start values in the docs.

* Use helper function for conversion to ternary ints
2021-04-22 11:32:45 +02:00
Adriane Boyd
e6b7600adf
Fix parser sourcing in NER converter (#7631) 2021-04-08 12:25:03 +02:00
Sofie Van Landeghem
204c2f116b
Extend score_spans for overlapping & non-labeled spans (#7209)
* extend span scorer with consider_label and allow_overlap

* unit test for spans y2x overlap

* add score_spans unit test

* docs for new fields in scorer.score_spans

* rename to include_label

* spell out if-else for clarity

* rename to 'labeled'

Co-authored-by: Adriane Boyd <adrianeboyd@gmail.com>
2021-04-08 12:19:17 +02:00
Paul O'Leary McCann
c362006cb9
Fix is_sent_start when converting from JSON (fix #7635) (#7655)
Data in the JSON format is split into sentences, and each sentence is
saved with is_sent_start flags. Currently the flags are 1 for the first
token and 0 for the others. When deserialized this results in a pattern
of True, None, None, None... which makes single-sentence documents look
as though they haven't had sentence boundaries set.

Since items saved in JSON format have been split into sentences already,
the is_sent_start values should all be True or False.
2021-04-08 18:24:52 +10:00
Adriane Boyd
ff84075839
Support large/infinite training corpora (#7208)
* Support infinite generators for training corpora

Support a training corpus with an infinite generator in the `spacy
train` training loop:

* Revert `create_train_batches` to the state where an infinite generator
can be used as the in the first epoch of exactly one epoch without
resulting in a memory leak (`max_epochs != 1` will still result in a
memory leak)
* Move the shuffling for the first epoch into the corpus reader,
renaming it to `spacy.Corpus.v2`.

* Switch to training option for shuffling in memory

Training loop:

* Add option `training.shuffle_train_corpus_in_memory` that controls
whether the corpus is loaded in memory once and shuffled in the training
loop
  * Revert changes to `create_train_batches` and rename to
`create_train_batches_with_shuffling` for use with `spacy.Corpus.v1` and
a corpus that should be loaded in memory
  * Add `create_train_batches_without_shuffling` for a corpus that
should not be shuffled in the training loop: the corpus is merely
batched during training

Corpus readers:

* Restore `spacy.Corpus.v1`
* Add `spacy.ShuffledCorpus.v1` for a corpus shuffled in memory in the
reader instead of the training loop
  * In combination with `shuffle_train_corpus_in_memory = False`, each
epoch could result in a different augmentation

* Refactor create_train_batches, validation

* Rename config setting to `training.shuffle_train_corpus`
* Refactor to use a single `create_train_batches` method with a
`shuffle` option
* Only validate `get_examples` in initialize step if:
  * labels are required
  * labels are not provided

* Switch back to max_epochs=-1 for streaming train corpus

* Use first 100 examples for stream train corpus init

* Always check validate_get_examples in initialize
2021-04-08 18:08:04 +10:00
Paul O'Leary McCann
7944761ba7
Add warning if initial vectors are empty (#7641)
See #7637, where this came up.
2021-04-04 20:20:24 +02:00
Ayush Chaurasia
3c2ce41dd8
W&B integration: Optional support for dataset and model checkpoint logging and versioning (#7429)
* Add optional artifacts logging

* Update docs

* Update spacy/training/loggers.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update spacy/training/loggers.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Update spacy/training/loggers.py

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>

* Bump WandbLogger Version

* Add documentation of v1 to legacy docs

* bump spacy-legacy to 3.0.2 (to be released)

Co-authored-by: Sofie Van Landeghem <svlandeg@users.noreply.github.com>
Co-authored-by: svlandeg <sofie.vanlandeghem@gmail.com>
2021-04-01 19:36:23 +02:00
Ines Montani
4bd3d01aaf
Merge pull request #7471 from polm/fix/listener-warnings 2021-03-22 12:45:02 +01:00
Adriane Boyd
48b90c8e1c Update deprecated doc.is_sentenced in Corpus 2021-03-19 09:43:52 +01:00
Lukas Winkler
3c362ac520
replace "is not" with != 2021-03-18 21:09:11 +01:00
Paul O'Leary McCann
40bc01e668 Proactively remove unused listeners
With this the changes in initialize.py might be unecessary.

Requires testing.
2021-03-17 22:41:41 +09:00
Paul O'Leary McCann
ef77c88638 Don't warn about components not in the pipeline
See here:

https://github.com/explosion/spaCy/discussions/7463

Still need to check if there are any side effects of listeners being
present but not in the pipeline, but this commit will silence the
warnings.
2021-03-17 14:56:04 +09:00
Adriane Boyd
3f3e8110dc
Fix lowercase augmentation (#7336)
* Fix aborted/skipped augmentation for `spacy.orth_variants.v1` if
lowercasing was enabled for an example
* Simplify `spacy.orth_variants.v1` for `Example` vs. `GoldParse`
* Preserve reference tokenization in `spacy.lower_case.v1`
2021-03-09 14:02:32 +11:00
Sofie Van Landeghem
cd70c3cb79
Fixing pretrain (#7342)
* initialize NLP with train corpus

* add more pretraining tests

* more tests

* function to fetch tok2vec layer for pretraining

* clarify parameter name

* test different objectives

* formatting

* fix check for static vectors when using vectors objective

* clarify docs

* logger statement

* fix init_tok2vec and proc.initialize order

* test training after pretraining

* add init_config tests for pretraining

* pop pretraining block to avoid config validation errors

* custom errors
2021-03-09 14:01:13 +11:00