Docling/docling/pipeline/base_pipeline.py
Christoph Auer 2a2c65bf4f
feat: Add pipeline timings and toggle visualization, establish debug settings (#183)
* Add settings to turn visualization on or off

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Add profiling code to all models

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Refactor and fix profiling codes

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Visualization codes output PNG to debug dir

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Fixes for time logging

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Optimize imports

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Update lockfile

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

* Add start_timestamps to ProfilingItem

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>

---------

Signed-off-by: Christoph Auer <cau@zurich.ibm.com>
2024-10-30 15:04:19 +01:00

190 lines
7.0 KiB
Python

import functools
import logging
import time
import traceback
from abc import ABC, abstractmethod
from typing import Callable, Iterable, List
from docling_core.types.doc import DoclingDocument, NodeItem
from docling.backend.abstract_backend import AbstractDocumentBackend
from docling.backend.pdf_backend import PdfDocumentBackend
from docling.datamodel.base_models import (
ConversionStatus,
DoclingComponentType,
ErrorItem,
Page,
)
from docling.datamodel.document import ConversionResult, InputDocument
from docling.datamodel.pipeline_options import PipelineOptions
from docling.datamodel.settings import settings
from docling.models.base_model import BaseEnrichmentModel
from docling.utils.profiling import ProfilingScope, TimeRecorder
from docling.utils.utils import chunkify
_log = logging.getLogger(__name__)
class BasePipeline(ABC):
def __init__(self, pipeline_options: PipelineOptions):
self.pipeline_options = pipeline_options
self.build_pipe: List[Callable] = []
self.enrichment_pipe: List[BaseEnrichmentModel] = []
def execute(self, in_doc: InputDocument, raises_on_error: bool) -> ConversionResult:
conv_res = ConversionResult(input=in_doc)
_log.info(f"Processing document {in_doc.file.name}")
try:
with TimeRecorder(
conv_res, "pipeline_total", scope=ProfilingScope.DOCUMENT
):
# These steps are building and assembling the structure of the
# output DoclingDocument
conv_res = self._build_document(conv_res)
conv_res = self._assemble_document(conv_res)
# From this stage, all operations should rely only on conv_res.output
conv_res = self._enrich_document(conv_res)
conv_res.status = self._determine_status(conv_res)
except Exception as e:
conv_res.status = ConversionStatus.FAILURE
if raises_on_error:
raise e
return conv_res
@abstractmethod
def _build_document(self, conv_res: ConversionResult) -> ConversionResult:
pass
def _assemble_document(self, conv_res: ConversionResult) -> ConversionResult:
return conv_res
def _enrich_document(self, conv_res: ConversionResult) -> ConversionResult:
def _filter_elements(
doc: DoclingDocument, model: BaseEnrichmentModel
) -> Iterable[NodeItem]:
for element, _level in doc.iterate_items():
if model.is_processable(doc=doc, element=element):
yield element
with TimeRecorder(conv_res, "doc_enrich", scope=ProfilingScope.DOCUMENT):
for model in self.enrichment_pipe:
for element_batch in chunkify(
_filter_elements(conv_res.document, model),
settings.perf.elements_batch_size,
):
# TODO: currently we assume the element itself is modified, because
# we don't have an interface to save the element back to the document
for element in model(
doc=conv_res.document, element_batch=element_batch
): # Must exhaust!
pass
return conv_res
@abstractmethod
def _determine_status(self, conv_res: ConversionResult) -> ConversionStatus:
pass
@classmethod
@abstractmethod
def get_default_options(cls) -> PipelineOptions:
pass
@classmethod
@abstractmethod
def is_backend_supported(cls, backend: AbstractDocumentBackend):
pass
# def _apply_on_elements(self, element_batch: Iterable[NodeItem]) -> Iterable[Any]:
# for model in self.build_pipe:
# element_batch = model(element_batch)
#
# yield from element_batch
class PaginatedPipeline(BasePipeline): # TODO this is a bad name.
def _apply_on_pages(
self, conv_res: ConversionResult, page_batch: Iterable[Page]
) -> Iterable[Page]:
for model in self.build_pipe:
page_batch = model(conv_res, page_batch)
yield from page_batch
def _build_document(self, conv_res: ConversionResult) -> ConversionResult:
if not isinstance(conv_res.input._backend, PdfDocumentBackend):
raise RuntimeError(
f"The selected backend {type(conv_res.input._backend).__name__} for {conv_res.input.file} is not a PDF backend. "
f"Can not convert this with a PDF pipeline. "
f"Please check your format configuration on DocumentConverter."
)
# conv_res.status = ConversionStatus.FAILURE
# return conv_res
with TimeRecorder(conv_res, "doc_build", scope=ProfilingScope.DOCUMENT):
for i in range(0, conv_res.input.page_count):
conv_res.pages.append(Page(page_no=i))
try:
# Iterate batches of pages (page_batch_size) in the doc
for page_batch in chunkify(
conv_res.pages, settings.perf.page_batch_size
):
start_pb_time = time.time()
# 1. Initialise the page resources
init_pages = map(
functools.partial(self.initialize_page, conv_res), page_batch
)
# 2. Run pipeline stages
pipeline_pages = self._apply_on_pages(conv_res, init_pages)
for p in pipeline_pages: # Must exhaust!
pass
end_pb_time = time.time() - start_pb_time
_log.debug(f"Finished converting page batch time={end_pb_time:.3f}")
except Exception as e:
conv_res.status = ConversionStatus.FAILURE
trace = "\n".join(traceback.format_exception(e))
_log.warning(
f"Encountered an error during conversion of document {conv_res.input.document_hash}:\n"
f"{trace}"
)
raise e
finally:
# Always unload the PDF backend, even in case of failure
if conv_res.input._backend:
conv_res.input._backend.unload()
return conv_res
def _determine_status(self, conv_res: ConversionResult) -> ConversionStatus:
status = ConversionStatus.SUCCESS
for page in conv_res.pages:
if page._backend is None or not page._backend.is_valid():
conv_res.errors.append(
ErrorItem(
component_type=DoclingComponentType.DOCUMENT_BACKEND,
module_name=type(page._backend).__name__,
error_message=f"Page {page.page_no} failed to parse.",
)
)
status = ConversionStatus.PARTIAL_SUCCESS
return status
# Initialise and load resources for a page
@abstractmethod
def initialize_page(self, conv_res: ConversionResult, page: Page) -> Page:
pass