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# Code of Conduct
## Our Pledge
In the interest of fostering an open and welcoming environment, we as
contributors and maintainers pledge to make participation in our project and
our community a harassment-free experience for everyone, regardless of age, body
size, disability, ethnicity, sex characteristics, gender identity and expression,
level of experience, education, socio-economic status, nationality, personal
appearance, race, religion, or sexual identity and orientation.
## Our Standards
Examples of behavior that contributes to creating a positive environment
include:
* Using welcoming and inclusive language
* Being respectful of differing viewpoints and experiences
* Gracefully accepting constructive criticism
* Focusing on what is best for the community
* Showing empathy towards other community members
Examples of unacceptable behavior by participants include:
* The use of sexualized language or imagery and unwelcome sexual attention or
advances
* Trolling, insulting/derogatory comments, and personal or political attacks
* Public or private harassment
* Publishing others' private information, such as a physical or electronic
address, without explicit permission
* Other conduct which could reasonably be considered inappropriate in a
professional setting
## Our Responsibilities
Project maintainers are responsible for clarifying the standards of acceptable
behavior and are expected to take appropriate and fair corrective action in
response to any instances of unacceptable behavior.
Project maintainers have the right and responsibility to remove, edit, or
reject comments, commits, code, wiki edits, issues, and other contributions
that are not aligned to this Code of Conduct, or to ban temporarily or
permanently any contributor for other behaviors that they deem inappropriate,
threatening, offensive, or harmful.
## Scope
This Code of Conduct applies within all project spaces, and it also applies when
an individual is representing the project or its community in public spaces.
Examples of representing a project or community include using an official
project e-mail address, posting via an official social media account, or acting
as an appointed representative at an online or offline event. Representation of
a project may be further defined and clarified by project maintainers.
## Enforcement
Instances of abusive, harassing, or otherwise unacceptable behavior may be
reported by contacting the project team at <conduct@pytorch.org>. All
complaints will be reviewed and investigated and will result in a response that
is deemed necessary and appropriate to the circumstances. The project team is
obligated to maintain confidentiality with regard to the reporter of an incident.
Further details of specific enforcement policies may be posted separately.
Project maintainers who do not follow or enforce the Code of Conduct in good
faith may face temporary or permanent repercussions as determined by other
members of the project's leadership.
## Attribution
This Code of Conduct is adapted from the [Contributor Covenant][homepage], version 1.4,
available at https://www.contributor-covenant.org/version/1/4/code-of-conduct.html
[homepage]: https://www.contributor-covenant.org
For answers to common questions about this code of conduct, see
https://www.contributor-covenant.org/faq
# Contributing to Facebook AI Research Sequence-to-Sequence Toolkit (fairseq)
We want to make contributing to this project as easy and transparent as
possible.
## Pull Requests
We actively welcome your pull requests.
1. Fork the repo and create your branch from `master`.
2. If you've added code that should be tested, add tests.
3. If you've changed APIs, update the documentation.
4. Ensure the test suite passes.
5. Make sure your code lints.
6. If you haven't already, complete the Contributor License Agreement ("CLA").
## Contributor License Agreement ("CLA")
In order to accept your pull request, we need you to submit a CLA. You only need
to do this once to work on any of Facebook's open source projects.
Complete your CLA here: <https://code.facebook.com/cla>
## Issues
We use GitHub issues to track public bugs. Please ensure your description is
clear and has sufficient instructions to be able to reproduce the issue.
## License
By contributing to Facebook AI Research Sequence-to-Sequence Toolkit (fairseq),
you agree that your contributions will be licensed under the LICENSE file in
the root directory of this source tree.
MIT License
Copyright (c) Facebook, Inc. and its affiliates.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
# @package _group_
common:
no_progress_bar: false
log_interval: 100
log_format: null
tensorboard_logdir: null
seed: 1
cpu: false
tpu: false
bf16: false
fp16: false
memory_efficient_fp16: false
memory_efficient_bf16: false
fp16_no_flatten_grads: false
fp16_init_scale: 128
fp16_scale_window: null
fp16_scale_tolerance: 0.0
min_loss_scale: 1.0e-4
threshold_loss_scale: null
user_dir: null
empty_cache_freq: 0
all_gather_list_size: 16384
model_parallel_size: 1
quantization_config_path: null
profile: false
distributed_training:
distributed_rank: 0
distributed_backend: "nccl"
distributed_init_method: null
distributed_port: -1
device_id: 0
local_rank: 0
distributed_no_spawn: false
ddp_backend: "c10d"
bucket_cap_mb: 25
fix_batches_to_gpus: false
find_unused_parameters: false
fast_stat_sync: false
broadcast_buffers: false
distributed_wrapper: "DDP"
slowmo_momentum: null
slowmo_algorithm: "LocalSGD"
localsgd_frequency: 3
dataset:
num_workers: 1
skip_invalid_size_inputs_valid_test: false
max_tokens: null
batch_size: null
required_batch_size_multiple: 8
dataset_impl: null
data_buffer_size: 10
train_subset: "train"
valid_subset: "valid"
validate_interval: 1
fixed_validation_seed: null
disable_validation: false
curriculum: 0
gen_subset: "test"
num_shards: 1
shard_id: 0
max_tokens_valid: ${dataset.max_tokens}
batch_size_valid: ${dataset.batch_size}
optimization:
max_epoch: 0
max_update: 0
clip_norm: 25.0
sentence_avg: false
update_freq: [ 1 ]
lr: [ 0.25 ]
min_lr: -1.0
use_bmuf: false
checkpoint:
save_dir: "checkpoints"
restore_file: "checkpoint_last.pt"
reset_dataloader: false
reset_lr_scheduler: false
reset_meters: false
reset_optimizer: false
optimizer_overrides: "{}"
save_interval: 1
save_interval_updates: 0
keep_interval_updates: -1
keep_last_epochs: -1
keep_best_checkpoints: -1
no_save: false
no_epoch_checkpoints: false
no_last_checkpoints: false
no_save_optimizer_state: false
best_checkpoint_metric: "loss"
maximize_best_checkpoint_metric: false
patience: -1
checkpoint_suffix: ""
bmuf:
block_lr: 1
block_momentum: 0.875
global_sync_iter: 50
warmup_iterations: 500
use_nbm: false
average_sync: false
defaults:
- task: language_modeling
- model: null
- criterion: null
- optimizer: null
- lr_scheduler: null
- bpe: null
- tokenizer: null
- scoring: null
- generation: null
- common_eval: null
- eval_lm: null
# @package _group_
sentence_avg: ${optimization.sentence_avg}
ddp_backend: ${distributed_training.ddp_backend}
# @package _group_
sentence_avg: ${optimization.sentence_avg}
# @package _group_
warmup_updates: 0
warmup_init_lr: -1
max_lr: 1.0
t_mult: 1.0
lr_period_updates: -1
lr_shrink: 0.1
# @package _group_
activation_fn: "relu"
dropout: 0.1
attention_dropout: 0.0
activation_dropout: 0.0
relu_dropout: 0.0
decoder_embed_dim: 512
decoder_output_dim: 512
decoder_input_dim: 512
decoder_ffn_embed_dim: 2048
decoder_layers: 6
decoder_attention_heads: 8
decoder_normalize_before: true
no_decoder_final_norm: false
adaptive_softmax_cutoff: null
adaptive_softmax_dropout: 0
adaptive_softmax_factor: 4
no_token_positional_embeddings: false
share_decoder_input_output_embed: false
character_embeddings: false
character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
character_embedding_dim: 4
char_embedder_highway_layers: 2
adaptive_input: false
adaptive_input_factor: 4
adaptive_input_cutoff: null
tie_adaptive_weights: false
tie_adaptive_proj: false
decoder_learned_pos: false
decoder_layerdrop: 0
decoder_layers_to_keep: null
layernorm_embedding: false
no_scale_embedding: false
quant_noise_pq: 0
quant_noise_pq_block_size: 8
quant_noise_scalar: 0
# @package _group_
activation_fn: "relu"
dropout: 0.1
attention_dropout: 0.1
activation_dropout: 0.0
relu_dropout: 0.0
decoder_embed_dim: 512
decoder_output_dim: 512
decoder_input_dim: 512
decoder_ffn_embed_dim: 4096
decoder_layers: 12
decoder_attention_heads: 16
decoder_normalize_before: true
no_decoder_final_norm: true
adaptive_softmax_cutoff: null
adaptive_softmax_dropout: 0
adaptive_softmax_factor: 4
no_token_positional_embeddings: false
share_decoder_input_output_embed: false
character_embeddings: false
character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
character_embedding_dim: 4
char_embedder_highway_layers: 2
adaptive_input: false
adaptive_input_factor: 4
adaptive_input_cutoff: null
tie_adaptive_weights: false
tie_adaptive_proj: false
decoder_learned_pos: false
decoder_layerdrop: 0
decoder_layers_to_keep: null
layernorm_embedding: false
no_scale_embedding: false
quant_noise_pq: 0
quant_noise_pq_block_size: 8
quant_noise_scalar: 0
# @package _group_
activation_fn: "relu"
dropout: 0.3
attention_dropout: 0.1
activation_dropout: 0.1
relu_dropout: 0.1
decoder_embed_dim: 1024
decoder_output_dim: 1024
decoder_input_dim: 1024
decoder_ffn_embed_dim: 4096
decoder_layers: 16
decoder_attention_heads: 8
decoder_normalize_before: true
no_decoder_final_norm: true
adaptive_softmax_cutoff: "20000,60000"
adaptive_softmax_dropout: 0.2
adaptive_softmax_factor: 4
no_token_positional_embeddings: false
share_decoder_input_output_embed: false
character_embeddings: false
character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
character_embedding_dim: 4
char_embedder_highway_layers: 2
adaptive_input: true
adaptive_input_factor: 4
adaptive_input_cutoff: "20000,60000"
tie_adaptive_weights: true
tie_adaptive_proj: true
decoder_learned_pos: false
decoder_layerdrop: 0
decoder_layers_to_keep: null
layernorm_embedding: false
no_scale_embedding: false
quant_noise_pq: 0
quant_noise_pq_block_size: 8
quant_noise_scalar: 0
# @package _group_
activation_fn: "relu"
dropout: 0.1
attention_dropout: 0.0
activation_dropout: 0.0
relu_dropout: 0.0
decoder_embed_dim: 1024
decoder_output_dim: 1024
decoder_input_dim: 1024
decoder_ffn_embed_dim: 4096
decoder_layers: 12
decoder_attention_heads: 16
decoder_normalize_before: true
no_decoder_final_norm: false
adaptive_softmax_cutoff: null
adaptive_softmax_dropout: 0
adaptive_softmax_factor: 4
no_token_positional_embeddings: false
share_decoder_input_output_embed: false
character_embeddings: false
character_filters: "[(1, 64), (2, 128), (3, 192), (4, 256), (5, 256), (6, 256), (7, 256)]"
character_embedding_dim: 4
char_embedder_highway_layers: 2
adaptive_input: false
adaptive_input_factor: 4
adaptive_input_cutoff: null
tie_adaptive_weights: false
tie_adaptive_proj: false
decoder_learned_pos: false
decoder_layerdrop: 0
decoder_layers_to_keep: null
layernorm_embedding: false
no_scale_embedding: false
quant_noise_pq: 0
quant_noise_pq_block_size: 8
quant_noise_scalar: 0
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