TST/CLN: Fix unit tests #693

…derUMAP_eval_audio_cbin_annot_notmat.toml

…l, stops generate-test-data script from crashing

…ts/fixtures/spect.py

…Net'; fix reference to Metadata in tests/test_datasets/test_window_dataset/conftest.py

…rever

…oderUMAP_train_audio_cbin_annot_notmat.toml to make training run faster

…ataset.py

…ix unit tests

…ification/test_window_dataset.py

…in tests/test_models/test_decorator.py

…lper module no longer exists

…n tests/test_prep/test_audio_dataset.py

…rays.py

…n/learncurve.py

…s.py

…config_metadata'

… throughout tests

…metadata.py

…g/test_parse.py

…me_classification/metadata.py

…indow_dataset.py

…t_sequence_dataset.py, fix unit test

…cation.py

…est_frame_classification.py

…on.py

…curve/frame_classification.py

…e num_input_channels + num_freqbins, not input_shape

…of the docstrings there

…st_decorator.py

…assification_model.py so that it doesn't fail

…ftest.py

…t_frame_classification_model.py and fix tests

…- previous way was unneccesarily convoluted

…e models it registers -- this way we don't raise errors in other unit tests because MockModel is already registered

…eetynet.py

…ing -- was unused anyway

…map.py -- deciding to not do this

…_eval_audio_cbin_annot_notmat.toml

…/parametric_umap.py

…arametric_umap.py

…that there's no issue with input shape being different that will lead to cryptic 'incorrect parameter size' errors when we re-load the checkpoint

- Import annotations from __future__ to be able to use pipe for type annotations - Add type annotations to `purpose_from_toml` - Change `Path` -> `pathlib.Path`, to be explicit

…tion

…dio_cbin_annot_notmat.toml so that we can re-use the same dataset for the eval config

…atting in docstrings

…ation.Metadata' in tests/test_predict/test_frame_classification.py

- Fix order of parameters to `prep_audio_dataset` - Fix type annotation, remove default for parameter `data_dir` - Also fix parameter ordering in docstring - Fix validation of `data_dir` in pre-condition section of function - Use `vak.common.typing.PathLike` for type hint

…ants in tests where needed, to parametrize specific unit tests

…orrectly -- need to add more cases to parametrize

…rom train_ in vak/train/__init__.py and write 'vak.train.train', but *also* use unitest.mock.patch on functions where they are looked up in the train_ module

…rain_.py

…so we don't loop unneccesarily through all configs

… since we're mocking anyways

…_models/test_frame_classification_model.py

…indow_dataset.py

…ional.py

…nvencoder_umap.py

…and fix function so that it does not add 'index' or 'level_0' columns to dataframes

…rrays.py

…x on returned dataframe

…ssification/dataset_arrays.py

…ion/learncurve.py

…ssification.py

…e in config files in test data

…tasets/frame_classification/metadata.py

…fine at module level so we can import those in tests where needed to parametrize

…est_prep/test_split/test_split.py

…/test_split.py

…io_dataset.py for clarity

…ype annotations, in src/vak/prep/spectrogram_dataset/spect_helper.py

…bber names of fixtures in other modules

…NPZ so that we are using a specific 'spectrograms_generated' directory' inside a dataset dir

…ect_helper.py, and no longer do recursive glob of spect_dir

…st_spect_helper.py

…p/test_spectrogram_dataset/test_spect_helper.py

…curve.py

…st_prep.py

…_dataset/test_spect_helper.py

…models, remove inappropriate asserts

…mand-line arg 'models'

…nerating test data

… reduce checkpoint size

…run it

… test that cli calls the right function

…xture -- we just need to test that cli calls the right function

…ure -- we just need to test that cli calls the right function

…ixture -- we're not testing something model specific here

…t set to None

…use 'model' fixture -- we don't want to use ConvEncoderUMAP model here

… to None

…n pyproject.toml

…ametrized model_name instead of model fixture

… not set to None

…set to None

… locally parametrized 'model_name' instead of model fixture

…arametrized 'model_name' instead of model fixture

… locally parametrized 'model_name' instead of model fixture

…lly parametrized 'model_name' instead of model fixture

…for_tests/configs that makes a 'tiny' TweetyNet

…configs/configs.json after deleting those configs

… tests/data_for_tests/configs that makes a 'tiny' ConvEncoder

…est_teenytweetynet.py

… .toml file so we don't get tensor size mismatch errors

…because fixing it will require fixing/changing how we parse config files

…t to None

…_eval.py instead of 'model' fixture that was removed

…was removed

… less-used sessions specific to test data at bottom. Remove use of model argument in test and coverage sessions, since that fixture was removed

…on/frame_classification.py

…rametric_umap.py

…thub/workflows/ci-linux.yml -- arg no longer used in that session

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TST/CLN: Fix unit tests #693

TST/CLN: Fix unit tests #693

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