From 3f15c67d3b1e64033565192bc4a84b9de2d1c345 Mon Sep 17 00:00:00 2001 From: John Giorgi Date: Mon, 27 May 2024 13:52:58 -0400 Subject: [PATCH] Fix broken streamlit (#392) * fix: rename pubmed bert everywhere * build: pin python to <3.10 * fix: use custom load archive to fix model naming issue * build: try bumping poetry build action * build: allow macos failures in ci --- .github/workflows/ci.yml | 11 +- poetry.lock | 6800 +++++++++++++++-------------- pyproject.toml | 3 +- seq2rel/seq2rel.py | 110 +- test_fixtures/experiment.jsonnet | 2 +- training_config/cdr.jsonnet | 2 +- training_config/cdr_hints.jsonnet | 2 +- training_config/dgm.jsonnet | 2 +- training_config/dgm_hints.jsonnet | 2 +- training_config/gda.jsonnet | 2 +- training_config/gda_hints.jsonnet | 2 +- 11 files changed, 3531 insertions(+), 3407 deletions(-) diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml index 888787b..0e2b8cb 100644 --- a/.github/workflows/ci.yml +++ b/.github/workflows/ci.yml @@ -11,12 +11,17 @@ on: jobs: build: - runs-on: ${{ matrix.os }} strategy: + fail-fast: false matrix: os: [ubuntu-latest, macos-latest] python-version: [3.8, 3.9] + include: + - os: macos-latest + allow-failure: true + - os: ubuntu-latest + allow-failure: false steps: - uses: actions/checkout@v3 @@ -25,7 +30,7 @@ jobs: with: python-version: ${{ matrix.python-version }} - name: Install Poetry - uses: abatilo/actions-poetry@v2.1.5 + uses: abatilo/actions-poetry@v3.0.0 - name: Install dependencies with Poetry run: | poetry install @@ -52,4 +57,4 @@ jobs: # very reliable but we don't want to report a failure # in the github UI just because the coverage report failed to # be published. - fail_ci_if_error: false \ No newline at end of file + fail_ci_if_error: false diff --git a/poetry.lock b/poetry.lock index 94fc428..72bfc0e 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,30 +1,111 @@ +# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. + [[package]] name = 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"^3.8" +python = "^3.8,<3.10" typer = { extras = ["all"], version = "^0.4.0" } validators = "^0.20.0" more-itertools = "^8.10.0" @@ -58,6 +58,7 @@ codecov = "^2.1.12" # Required to run the demo. Streamlit installs all dev dependencies, so we stick them here. streamlit = "^1.12.0" pyvis = "^0.2.1" +altair = "^4.0.0" # This configuration is adapted from: https://github.com/allenai/allennlp/blob/main/pyproject.toml [tool.black] diff --git a/seq2rel/seq2rel.py b/seq2rel/seq2rel.py index ab8df35..bee9c92 100644 --- a/seq2rel/seq2rel.py +++ b/seq2rel/seq2rel.py @@ -1,16 +1,24 @@ +import logging +import os +import shutil +from os import PathLike from pathlib import Path -from typing import Any, List, Optional, Union +from typing import Any, Dict, List, Optional, Union import torch from allennlp.common import util as common_util from allennlp.common.file_utils import cached_path -from allennlp.models.archival import load_archive +from allennlp.common.meta import Meta +from allennlp.common.params import Params +from allennlp.models import archival from allennlp.predictors import Predictor from more_itertools import chunked from validators.url import url from seq2rel.common.util import sanitize_text +logger = logging.getLogger(__name__) + PRETRAINED_MODELS = { "cdr": "https://github.com/JohnGiorgi/seq2rel/releases/download/pretrained-models/cdr.tar.gz", "cdr_hints": "https://github.com/JohnGiorgi/seq2rel/releases/download/pretrained-models/cdr_hints.tar.gz", @@ -21,6 +29,103 @@ "docred": "https://github.com/JohnGiorgi/seq2rel/releases/download/pretrained-models/docred.tar.gz", } +# Needed strictly to rename +# microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext with +# microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext +# otherwise identical to allennlp.models.archival.load_archive +def load_archive( + archive_file: Union[str, PathLike], + cuda_device: int = -1, + overrides: Union[str, Dict[str, Any]] = "", + weights_file: str = None, +) -> archival.Archive: + """ + Instantiates an Archive from an archived `tar.gz` file. + + # Parameters + + archive_file : `Union[str, PathLike]` + The archive file to load the model from. + cuda_device : `int`, optional (default = `-1`) + If `cuda_device` is >= 0, the model will be loaded onto the + corresponding GPU. Otherwise it will be loaded onto the CPU. + overrides : `Union[str, Dict[str, Any]]`, optional (default = `""`) + JSON overrides to apply to the unarchived `Params` object. + weights_file : `str`, optional (default = `None`) + The weights file to use. If unspecified, weights.th in the archive_file will be used. + """ + # redirect to the cache, if necessary + resolved_archive_file = cached_path(archive_file) + + if resolved_archive_file == archive_file: + logger.info(f"loading archive file {archive_file}") + else: + logger.info(f"loading archive file {archive_file} from cache at {resolved_archive_file}") + + meta: Optional[Meta] = None + + tempdir = None + try: + if os.path.isdir(resolved_archive_file): + serialization_dir = resolved_archive_file + else: + with archival.extracted_archive(resolved_archive_file, cleanup=False) as tempdir: + serialization_dir = tempdir + + if weights_file: + weights_path = weights_file + else: + weights_path = archival.get_weights_path(serialization_dir) + + # Load config + config = Params.from_file(os.path.join(serialization_dir, archival.CONFIG_NAME), overrides) + + # Rename + # microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext with + # microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext + def rename_pretrained_model(config: Params) -> Params: + for key, value in config.items(): + if isinstance(value, dict): + rename_pretrained_model(value) + else: + if value == "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext": + config[ + key + ] = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext" + + config = config.as_dict() + rename_pretrained_model(config) + config = Params(config) + + # Instantiate model and dataset readers. Use a duplicate of the config, as it will get consumed. + dataset_reader, validation_dataset_reader = archival._load_dataset_readers( + config.duplicate(), serialization_dir + ) + model = archival._load_model( + config.duplicate(), weights_path, serialization_dir, cuda_device + ) + + # Load meta. + meta_path = os.path.join(serialization_dir, archival.META_NAME) + if os.path.exists(meta_path): + meta = Meta.from_path(meta_path) + finally: + if tempdir is not None: + logger.info(f"removing temporary unarchived model dir at {tempdir}") + shutil.rmtree(tempdir, ignore_errors=True) + + # Check version compatibility. + if meta is not None: + archival._check_version_compatibility(archive_file, meta) + + return archival.Archive( + model=model, + config=config, + dataset_reader=dataset_reader, + validation_dataset_reader=validation_dataset_reader, + meta=meta, + ) + class Seq2Rel: """A simple interface to the model for the purposes of extracting entities and relations from text. @@ -82,6 +187,7 @@ def __init__(self, pretrained_model_name_or_path: str, **kwargs: Any) -> None: overrides = { "model.source_embedder.token_embedders.tokens.load_weights": False, } + # Allow user to update these with kwargs. if "overrides" in kwargs: overrides.update(kwargs.pop("overrides")) diff --git a/test_fixtures/experiment.jsonnet b/test_fixtures/experiment.jsonnet index 0118845..335c1e9 100644 --- a/test_fixtures/experiment.jsonnet +++ b/test_fixtures/experiment.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 16; // Max length of input text diff --git a/training_config/cdr.jsonnet b/training_config/cdr.jsonnet index 8468577..70e59a4 100644 --- a/training_config/cdr.jsonnet +++ b/training_config/cdr.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 512; // Max length of input text diff --git a/training_config/cdr_hints.jsonnet b/training_config/cdr_hints.jsonnet index 148fda0..e91d354 100644 --- a/training_config/cdr_hints.jsonnet +++ b/training_config/cdr_hints.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 512; // Max length of input text diff --git a/training_config/dgm.jsonnet b/training_config/dgm.jsonnet index f028b97..c84876d 100644 --- a/training_config/dgm.jsonnet +++ b/training_config/dgm.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 512; // Max length of input text diff --git a/training_config/dgm_hints.jsonnet b/training_config/dgm_hints.jsonnet index 8e0204a..abf391b 100644 --- a/training_config/dgm_hints.jsonnet +++ b/training_config/dgm_hints.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 512; // Max length of input text diff --git a/training_config/gda.jsonnet b/training_config/gda.jsonnet index 68e0462..1b890f8 100644 --- a/training_config/gda.jsonnet +++ b/training_config/gda.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 512; // Max length of input text diff --git a/training_config/gda_hints.jsonnet b/training_config/gda_hints.jsonnet index 0474f24..4d15567 100644 --- a/training_config/gda_hints.jsonnet +++ b/training_config/gda_hints.jsonnet @@ -3,7 +3,7 @@ // The pretrained model to use as encoder. This is a reasonable default for biomedical text. // Should be a registered name in the Transformers library (see https://huggingface.co/models) // OR a path on disk to a serialized transformer model. -local model_name = "microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext"; +local model_name = "microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext"; // These are reasonable defaults. local max_length = 512; // Max length of input text