339 lines
11 KiB
Markdown
339 lines
11 KiB
Markdown
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# RKNNToolkit2 API Difference With Toolkit1
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## rknn.config
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- Toolkit1:
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config(batch_size=100, # abandoned
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caffe_mean_file=None, # abandoned
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dtype='float32', # abandoned
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epochs=-1, # abandoned
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force_gray=None, # abandoned
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input_fitting='scale', # abandoned
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input_normalization=None, # abandoned
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mean_file=None, # abandoned
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model_data_format='zone', # abandoned
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model_quantize=None, # abandoned
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optimize='Default', # abandoned
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quantized_dtype='asymmetric_affine-u8',
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quantized_moving_alpha=0.01, # abandoned
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quantized_algorithm='normal',
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quantized_divergence_nbins=1024, # abandoned
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mmse_epoch=3, # abandoned
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random_brightness=None, # abandoned
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random_contrast=None, # abandoned
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random_crop=None, # abandoned
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random_flip=None, # abandoned
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random_mirror=None, # abandoned
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reorder_channel=None, # abandoned
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restart=False, # abandoned
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samples=-1, # abandoned
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need_horizontal_merge=False, # abandoned
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deconv_merge=True, # abandoned
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conv_mul_merge=True, # abandoned
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quantized_hybrid=False, # abandoned
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output_optimize=0, # abandoned
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remove_tensorflow_output_permute=False, # abandoned
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optimization_level=3,
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target_platform=None,
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mean_values=None,
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std_values=None,
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channel_mean_value=None, # abandoned
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force_builtin_perm=False, # abandoned
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do_sparse_network=True, # abandoned
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merge_dequant_layer_and_output_node=False, # abandoned
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quantize_input_node=False, # abandoned
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inputs_scale_range=None) # abandoned
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- Toolkit2:
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config(mean_values=None,
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std_values=None,
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quantized_dtype='asymmetric_quantized-8',
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quantized_algorithm='normal',
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quantized_method='channel', # new
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target_platform=None,
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quant_img_RGB2BGR=False, # new
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float_dtype='float16', # new
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optimization_level=3,
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custom_string=None, # new
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remove_weight=False, # new
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compress_weight=False, # new
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inputs_yuv_fmt=None, # new
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single_core_mode=False) # new
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- In addition to the above abandoned/new items, there are other differences:
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quantized_dtype:
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toolkit1: asymmetric_affine-u8, dynamic_fixed_point-i8, dynamic_fixed_point-i16
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toolkit2: asymmetric_quantized-8
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quantized_algorithm:
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toolkit1: normal(default), mmse, kl_divergence, moving_average
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toolkit2: normal(default), mmse
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target_platform:
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toolkit1: rk1808, rk3399pro, rv1109, rv1126
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toolkit2: rk3566, rk3568, rk3588, rk3588s, rv1103, rv1106, rk3562 and newer
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## rknn.load_tensorflow
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- Toolkit1:
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load_tensorflow(tf_pb,
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inputs,
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input_size_list,
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outputs,
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predef_file=None, # abandoned
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mean_values=None, # abandoned
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std_values=None, # abandoned
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size_with_batch=None) # abandoned
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- Toolkit2:
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load_tensorflow(tf_pb,
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inputs,
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input_size_list,
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outputs)
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- In addition to the above abandoned items, there are other differences:
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inputs:
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toolkit1: node list (layer name)
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toolkit2: node list (operand name)
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outputs:
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toolkit1: node list (layer name)
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toolkit2: node list (operand name)
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## rknn.load_caffe
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- Toolkit1:
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load_caffe(model,
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proto, # abandoned
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blobs=None)
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- Toolkit2:
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load_caffe(model,
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blobs=None,
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input_name=None) # new
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## rknn.load_keras
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- Toolkit1:
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load_keras(model, convert_engine='Keras')
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- Toolkit2:
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Not supported yet!
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## rknn.load_pytorch
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- Toolkit1:
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load_pytorch(model,
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input_size_list=None,
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inputs=None, # abandoned
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outputs=None, # abandoned
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convert_engine='torch') # abandoned
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- Toolkit2:
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load_pytorch(model,
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input_size_list)
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## rknn.load_mxnet
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- Toolkit1:
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load_mxnet(symbol, params, input_size_list=None)
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- Toolkit2:
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Not supported yet!
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## rknn.build
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- Toolkit1:
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build(do_quantization=True,
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dataset='dataset.txt',
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pre_compile=False, # abandoned
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rknn_batch_size=-1)
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- Toolkit2:
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build(do_quantization=True,
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dataset='dataset.txt',
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rknn_batch_size=-1):
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## rknn.direct_build
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- Toolkit1:
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direct_build(model_input, data_input, model_quantize=None, pre_compile=False)
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- Toolkit2:
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Not supported yet!
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## rknn.hybrid_quantization_step1
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- Toolkit1:
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hybrid_quantization_step1(dataset=None)
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- Toolkit2:
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hybrid_quantization_step1(dataset=None,
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rknn_batch_size=-1, # new
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proposal=False, # new
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proposal_dataset_size=1) # new
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## rknn.hybrid_quantization_step2
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- Toolkit1:
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hybrid_quantization_step2(model_input,
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data_input,
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model_quantization_cfg,
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dataset, # abandoned
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pre_compile=False) # abandoned
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- Toolkit2:
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hybrid_quantization_step2(model_input,
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data_input,
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model_quantization_cfg)
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## rknn.accuracy_analysis
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- Toolkit1:
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accuracy_analysis(inputs,
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output_dir='./snapshot',
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calc_qnt_error=True, # abandoned
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target=None,
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device_id=None,
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dump_file_type='tensor') # abandoned
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- Toolkit2:
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accuracy_analysis(inputs,
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output_dir='./snapshot',
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target=None,
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device_id=None)
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## rknn.load_rknn
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- Toolkit1:
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load_rknn(path,
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load_model_in_npu=False) # abandoned
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- Toolkit2:
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load_rknn(path)
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## rknn.export_rknn
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- Toolkit1:
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export_rknn(export_path)
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- Toolkit2:
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export_rknn(export_path,
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**kwargs) # new
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## rknn.load_firmware
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- Toolkit1:
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load_firmware(fw_dir=None)
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- Toolkit2:
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Not supported yet!
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## rknn.init_runtime
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- Toolkit1:
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init_runtime(target=None,
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target_sub_class=None,
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device_id=None,
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perf_debug=False,
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eval_mem=False,
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async_mode=False,
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rknn2precompile=False) # abandoned
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- Toolkit2:
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init_runtime(target=None,
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target_sub_class=None,
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device_id=None,
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perf_debug=False,
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eval_mem=False,
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async_mode=False)
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- In addition to the above abandoned items, there are other differences:
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target:
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toolkit1: None(simulator), RK3399Pro, RK1808
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toolkit2: None(simulator), RK3566, RK3568, RK3588, RK3562
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## rknn.inference
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- Toolkit1:
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inference(inputs,
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data_type=None, # abandoned
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data_format=None,
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inputs_pass_through=None,
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get_frame_id=False)
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- Toolkit2:
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inference(inputs,
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data_format=None,
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inputs_pass_through=None,
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get_frame_id=False)
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## rknn.eval_perf
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- Toolkit1:
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eval_perf(inputs=None, # abandoned
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data_type=None, # abandoned
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data_format=None, # abandoned
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is_print=True,
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loop_cnt=1) # abandoned
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- Toolkit2:
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eval_perf(is_print=True)
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## rknn.export_rknn_precompile_model
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- Toolkit1:
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export_rknn_precompile_model(export_path=None)
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- Toolkit2:
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Abandoned
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## rknn.export_rknn_sync_model
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- Toolkit1:
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export_rknn_sync_model(input_model=None, sync_uids=None, output_model=None)
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- Toolkit2:
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Abandoned
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## rknn.register_op
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- Toolkit1:
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register_op(op_path)
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- Toolkit2:
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Not supported yet
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## rknn.fetch_rknn_model_config
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- Toolkit1:
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fetch_rknn_model_config(model_path)
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- Toolkit2:
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Not supported yet
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## rknn.list_support_target_platform
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- Toolkit1:
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list_support_target_platform(rknn_model=None)
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- Toolkit2:
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Not supported yet
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