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segmentation/deploy/configs/_base_/backends/tensorrt.py
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segmentation/deploy/configs/_base_/backends/tensorrt.py
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backend_config = dict(
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type='tensorrt', common_config=dict(fp16_mode=False, max_workspace_size=0))
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segmentation/deploy/configs/_base_/onnx_config.py
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segmentation/deploy/configs/_base_/onnx_config.py
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onnx_config = dict(
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type='onnx',
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export_params=True,
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keep_initializers_as_inputs=False,
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opset_version=11,
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save_file='end2end.onnx',
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input_names=['input'],
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output_names=['output'],
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input_shape=None,
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optimize=True)
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segmentation/deploy/configs/mmseg/segmentation_static.py
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segmentation/deploy/configs/mmseg/segmentation_static.py
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_base_ = ['../_base_/onnx_config.py']
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codebase_config = dict(type='mmseg', task='Segmentation', with_argmax=True)
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_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt.py']
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onnx_config = dict(input_shape=[512, 512])
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backend_config = dict(
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common_config=dict(max_workspace_size=1 << 30),
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model_inputs=[
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dict(
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input_shapes=dict(
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input=dict(
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min_shape=[1, 3, 512, 512],
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opt_shape=[1, 3, 512, 512],
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max_shape=[1, 3, 512, 512])))
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])
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