# Copyright (c) 2025 PaddlePaddle Authors. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. from ..utils.cli import ( add_simple_inference_args, get_subcommand_args, perform_simple_inference, str2bool, ) from .base import PaddleXPipelineWrapper, PipelineCLISubcommandExecutor from .utils import create_config_from_structure from paddlex.utils.pipeline_arguments import custom_type class DocUnderstanding(PaddleXPipelineWrapper): def __init__( self, doc_understanding_model_name=None, doc_understanding_model_dir=None, doc_understanding_batch_size=None, **kwargs, ): self._params = { "doc_understanding_model_name": doc_understanding_model_name, "doc_understanding_model_dir": doc_understanding_model_dir, "doc_understanding_batch_size": doc_understanding_batch_size, } super().__init__(**kwargs) @property def _paddlex_pipeline_name(self): return "doc_understanding" def predict( self, input, **kwargs, ): result = [] for res in self.paddlex_pipeline.predict(input, **kwargs): result.append(res) return result @classmethod def get_cli_subcommand_executor(cls): return DocUnderstandingCLISubcommandExecutor() def _get_paddlex_config_overrides(self): STRUCTURE = { "SubModules.DocUnderstanding.model_name": self._params[ "doc_understanding_model_name" ], "SubModules.DocUnderstanding.model_dir": self._params[ "doc_understanding_model_dir" ], "SubModules.DocUnderstanding.batch_size": self._params[ "doc_understanding_batch_size" ], } return create_config_from_structure(STRUCTURE) class DocUnderstandingCLISubcommandExecutor(PipelineCLISubcommandExecutor): input_validator = staticmethod(custom_type(dict)) @property def subparser_name(self): return "doc_understanding" def _update_subparser(self, subparser): add_simple_inference_args(subparser) subparser.add_argument( "--doc_understanding_model_name", type=str, help="Name of the document understanding model.", ) subparser.add_argument( "--doc_understanding_model_dir", type=str, help="Path to the document understanding model directory.", ) subparser.add_argument( "--doc_understanding_batch_size", type=str, help="Batch size for the document understanding model.", ) def execute_with_args(self, args): params = get_subcommand_args(args) params["input"] = self.input_validator(params["input"]) perform_simple_inference(DocUnderstanding, params)