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How to use _try_validate method in pandera

Best Python code snippet using pandera_python

pt_linen_validate.py

Source:pt_linen_validate.py

...69    args = parser.parse_args()70    print('JAX host: %d / %d' % (jax.host_id(), jax.host_count()))71    print('JAX devices:\n%s' % '\n'.join(str(d) for d in jax.devices()), flush=True)72    jax.config.enable_omnistaging()73    def _try_validate(args):74        res = None75        batch_size = args.batch_size76        while res is None:77            try:78                print(f'Setting validation batch size to {batch_size}')79                args.batch_size = batch_size80                res = validate(args)81            except RuntimeError as e:82                if batch_size <= 1:83                    print("Validation failed with no ability to reduce batch size. Exiting.")84                    raise e85                batch_size = max(batch_size // 2, 1)86                print("Validation failed, reducing batch size by 50%")87        return res88    if get_model_cfg(args.model) is not None:89        _try_validate(args)90    else:91        models = list_models(pretrained=True)92        if args.model != 'all':93            models = fnmatch.filter(models, args.model)94        if not models:95            print(f'ERROR: No models found to validate with pattern {args.model}.')96            exit(1)97        print('Validating:', ', '.join(models))98        results = []99        start_batch_size = args.batch_size100        for m in models:101            args.batch_size = start_batch_size  # reset in case reduced for retry102            args.model = m103            res = _try_validate(args)104            res.update(dict(model=m))105            results.append(res)106        print('Results:')107        for r in results:108            print(f"Model: {r['model']}, Top1: {r['top1']}, Top5: {r['top5']}")109if __name__ == '__main__':...

pt_objax_validate.py

Source:pt_objax_validate.py

...65def main():66    args = parser.parse_args()67    print('JAX host: %d / %d' % (jax.host_id(), jax.host_count()))68    print('JAX devices:\n%s' % '\n'.join(str(d) for d in jax.devices()), flush=True)69    def _try_validate(args):70        res = None71        batch_size = args.batch_size72        while res is None:73            try:74                print(f'Setting validation batch size to {batch_size}')75                args.batch_size = batch_size76                res = validate(args)77            except RuntimeError as e:78                if batch_size <= 1:79                    print("Validation failed with no ability to reduce batch size. Exiting.")80                    raise e81                batch_size = max(batch_size // 2, 1)82                print("Validation failed, reducing batch size by 50%")83        return res84    if get_model_cfg(args.model) is not None:85        _try_validate(args)86    else:87        models = list_models(pretrained=True)88        if args.model != 'all':89            models = fnmatch.filter(models, args.model)90        if not models:91            print(f'ERROR: No models found to validate with pattern {args.model}.')92            exit(1)93        print('Validating:', ', '.join(models))94        results = []95        start_batch_size = args.batch_size96        for m in models:97            args.batch_size = start_batch_size  # reset in case reduced for retry98            args.model = m99            res = _try_validate(args)100            res.update(dict(model=m))101            results.append(res)102        print('Results:')103        for r in results:104            print(f"Model: {r['model']}, Top1: {r['top1']}, Top5: {r['top5']}")105if __name__ == '__main__':...

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