Spaces:
Runtime error
Runtime error
| # ########################################################################### | |
| # | |
| # CLOUDERA APPLIED MACHINE LEARNING PROTOTYPE (AMP) | |
| # (C) Cloudera, Inc. 2022 | |
| # All rights reserved. | |
| # | |
| # Applicable Open Source License: Apache 2.0 | |
| # | |
| # NOTE: Cloudera open source products are modular software products | |
| # made up of hundreds of individual components, each of which was | |
| # individually copyrighted. Each Cloudera open source product is a | |
| # collective work under U.S. Copyright Law. Your license to use the | |
| # collective work is as provided in your written agreement with | |
| # Cloudera. Used apart from the collective work, this file is | |
| # licensed for your use pursuant to the open source license | |
| # identified above. | |
| # | |
| # This code is provided to you pursuant a written agreement with | |
| # (i) Cloudera, Inc. or (ii) a third-party authorized to distribute | |
| # this code. If you do not have a written agreement with Cloudera nor | |
| # with an authorized and properly licensed third party, you do not | |
| # have any rights to access nor to use this code. | |
| # | |
| # Absent a written agreement with Cloudera, Inc. (“Cloudera”) to the | |
| # contrary, A) CLOUDERA PROVIDES THIS CODE TO YOU WITHOUT WARRANTIES OF ANY | |
| # KIND; (B) CLOUDERA DISCLAIMS ANY AND ALL EXPRESS AND IMPLIED | |
| # WARRANTIES WITH RESPECT TO THIS CODE, INCLUDING BUT NOT LIMITED TO | |
| # IMPLIED WARRANTIES OF TITLE, NON-INFRINGEMENT, MERCHANTABILITY AND | |
| # FITNESS FOR A PARTICULAR PURPOSE; (C) CLOUDERA IS NOT LIABLE TO YOU, | |
| # AND WILL NOT DEFEND, INDEMNIFY, NOR HOLD YOU HARMLESS FOR ANY CLAIMS | |
| # ARISING FROM OR RELATED TO THE CODE; AND (D)WITH RESPECT TO YOUR EXERCISE | |
| # OF ANY RIGHTS GRANTED TO YOU FOR THE CODE, CLOUDERA IS NOT LIABLE FOR ANY | |
| # DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, PUNITIVE OR | |
| # CONSEQUENTIAL DAMAGES INCLUDING, BUT NOT LIMITED TO, DAMAGES | |
| # RELATED TO LOST REVENUE, LOST PROFITS, LOSS OF INCOME, LOSS OF | |
| # BUSINESS ADVANTAGE OR UNAVAILABILITY, OR LOSS OR CORRUPTION OF | |
| # DATA. | |
| # | |
| # ########################################################################### | |
| from apps.data_utils import DATA_PACKET | |
| from src.style_transfer import StyleTransfer | |
| from src.style_classification import StyleIntensityClassifier | |
| from src.content_preservation import ContentPreservationScorer | |
| def load_and_cache_HF_models(style_data_packet): | |
| """ | |
| This utility function is used to download and cache models needed for all style | |
| attributes in `apps.data_utils.DATA_PACKET` | |
| Args: | |
| style_data_packet (dict) | |
| """ | |
| for style_data in style_data_packet.keys(): | |
| try: | |
| st = StyleTransfer(model_identifier=style_data.seq2seq_model_path) | |
| sic = StyleIntensityClassifier(style_data.cls_model_path) | |
| cps = ContentPreservationScorer( | |
| cls_model_identifier=style_data.cls_model_path, | |
| sbert_model_identifier=style_data.sbert_model_path, | |
| ) | |
| del st, sic, cps | |
| except Exception as e: | |
| print(e) | |
| if __name__=="__main__": | |
| load_and_cache_HF_models(DATA_PACKET) |