Make Pipeline printable

[mgoin]

Implements __str__ and __repr__ to make Pipeline show something useful when printed.

This PR just adds the config and engine to the printable properties - this covers most information. Also a small bugfix for Pipeline.to_config()

    def _properties_dict(self) -> Dict:
        return {
            "config": self.to_config(),
            "engine": self.engine,
        }

Example:

import deepsparse
pipe = deepsparse.Pipeline.create(task="text-generation", model_path="hf:mgoin/TinyStories-1M-deepsparse")
print(pipe)
### deepsparse.transformers.pipelines.text_generation.TextGenerationPipeline:
###         config: task='text_generation' model_path='hf:mgoin/TinyStories-1M-deepsparse' engine_type='deepsparse' batch_size=1 num_cores=None scheduler=None input_shapes=None alias=None kwargs={'input_schema': <class 'deepsparse.transformers.pipelines.text_generation.TextGenerationInput'>, 'output_schema': <class 'deepsparse.transformers.pipelines.text_generation.TextGenerationOutput'>}
###         engine: NLDecoderEngine: deepsparse.engine.Engine:
###         onnx_file_path: /home/mgoin/.cache/huggingface/hub/models--mgoin--TinyStories-1M-deepsparse/snapshots/62256599e36d99faefb58461e0030e19e1050ea1/model.onnx
###         batch_size: 1
###         num_cores: 18
###         num_streams: 1
###         scheduler: Scheduler.default
###         fraction_of_supported_ops: 1.0
###         cpu_avx_type: avx512
###         cpu_vnni: False

pipe = deepsparse.Pipeline.create(task="yolo")
print(pipe)
### deepsparse.yolo.pipelines.YOLOPipeline:
###         config: task='yolo' model_path='zoo:cv/detection/yolov5-l/pytorch/ultralytics/coco/pruned_quant-aggressive_95' engine_type='deepsparse' batch_size=1 num_cores=None scheduler=None input_shapes=None alias=None kwargs={'model_config': None, 'class_names': None, 'image_size': (640, 640), 'input_schema': <class 'deepsparse.yolo.schemas.YOLOInput'>, 'output_schema': <class 'deepsparse.yolo.schemas.YOLOOutput'>}
###         engine: deepsparse.engine.Engine:
###         onnx_file_path: /home/mgoin/.cache/sparsezoo/neuralmagic/yolov5-l-coco-pruned.4block_quantized/deployment/model.onnx
###         batch_size: 1
###         num_cores: 18
###         num_streams: 1
###         scheduler: Scheduler.default
###         fraction_of_supported_ops: 1.0
###         cpu_avx_type: avx512
###         cpu_vnni: False

[rahul-tuli]

😭 thank you for this