* improving generation
* finalized special token behaviour for no_beam_search generation
* solved modeling_utils merge conflict
* solve merge conflicts in modeling_utils.py
* add run_generation improvements from PR #2749
* adapted language generation to not use hardcoded -1 if no padding token is available
* remove the -1 removal as hard coded -1`s are not necessary anymore
* add lightweight language generation testing for randomely initialized models - just checking whether no errors are thrown
* add slow language generation tests for pretrained models using hardcoded output with pytorch seed
* delete ipdb
* check that all generated tokens are valid
* renaming
* renaming Generation -> Generate
* make style
* updated so that generate_beam_search has same token behavior than generate_no_beam_search
* consistent return format for run_generation.py
* deleted pretrain lm generate tests -> will be added in another PR
* cleaning of unused if statements and renaming
* run_generate will always return an iterable
* make style
* consistent renaming
* improve naming, make sure generate function always returns the same tensor, add docstring
* add slow tests for all lmhead models
* make style and improve example comments modeling_utils
* better naming and refactoring in modeling_utils
* improving generation
* finalized special token behaviour for no_beam_search generation
* solved modeling_utils merge conflict
* solve merge conflicts in modeling_utils.py
* add run_generation improvements from PR #2749
* adapted language generation to not use hardcoded -1 if no padding token is available
* remove the -1 removal as hard coded -1`s are not necessary anymore
* add lightweight language generation testing for randomely initialized models - just checking whether no errors are thrown
* add slow language generation tests for pretrained models using hardcoded output with pytorch seed
* delete ipdb
* check that all generated tokens are valid
* renaming
* renaming Generation -> Generate
* make style
* updated so that generate_beam_search has same token behavior than generate_no_beam_search
* consistent return format for run_generation.py
* deleted pretrain lm generate tests -> will be added in another PR
* cleaning of unused if statements and renaming
* run_generate will always return an iterable
* make style
* consistent renaming
* improve naming, make sure generate function always returns the same tensor, add docstring
* add slow tests for all lmhead models
* make style and improve example comments modeling_utils
* better naming and refactoring in modeling_utils
* changed fast random lm generation testing design to more general one
* delete in old testing design in gpt2
* correct old variable name
* temporary fix for encoder_decoder lm generation tests - has to be updated when t5 is fixed
* adapted all fast random generate tests to new design
* better warning description in modeling_utils
* better comment
* better comment and error message
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
This is the result of:
$ black --line-length 119 examples templates transformers utils hubconf.py setup.py
There's a lot of fairly long lines in the project. As a consequence, I'm
picking the longest widely accepted line length, 119 characters.
This is also Thomas' preference, because it allows for explicit variable
names, to make the code easier to understand.
adding conversion script
adding first draft of modeling & tokenization
adding placeholder for test files
bunch of changes
registering the tokenizer/model/etc
tests
change link; something is very VERY wrong here
weird end-of-word thingy going on
i think the tokenization works now ; wrote the unit tests
overall structure works;load w next
the monster is alive!
works after some cleanup as well
adding emacs autosave to gitignore
currently only supporting the 48 layer one; seems to infer fine on my macbook
cleanup
fixing some documentation
fixing some documentation
tests passing?
now works on CUDA also
adding greedy?
adding greedy sampling
works well
