add config module

configs/mmdet3d/voxel-detection/voxel-detection_dynamic.py

+_base_ = ['./voxel-detection_static.py']
+
+onnx_config = dict(
+    dynamic_axes={
+        'voxels': {
+            0: 'voxels_num',
+        },
+        'num_points': {
+            0: 'voxels_num',
+        },
+        'coors': {
+            0: 'voxels_num',
+        }
+    },
+    input_shape=None)

configs/mmdet3d/voxel-detection/voxel-detection_onnxruntime-fp16_dynamic.py

+_base_ = [
+    './voxel-detection_dynamic.py', '../../_base_/backends/onnxruntime-fp16.py'
+]

configs/mmdet3d/voxel-detection/voxel-detection_onnxruntime_dynamic.py

+_base_ = [
+    './voxel-detection_dynamic.py', '../../_base_/backends/onnxruntime.py'
+]

configs/mmdet3d/voxel-detection/voxel-detection_openvino_dynamic-kitti-32x4.py

+_base_ = ['./voxel-detection_dynamic.py', '../../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(model_inputs=[
+    dict(
+        opt_shapes=dict(
+            voxels=[5000, 32, 4], num_points=[5000], coors=[5000, 4]))
+])

configs/mmdet3d/voxel-detection/voxel-detection_openvino_dynamic-nus-20x5.py

+_base_ = ['./voxel-detection_dynamic.py', '../../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(model_inputs=[
+    dict(
+        opt_shapes=dict(
+            voxels=[20000, 20, 5], num_points=[20000], coors=[20000, 4]))
+])

configs/mmdet3d/voxel-detection/voxel-detection_openvino_dynamic-nus-64x4.py

+_base_ = ['./voxel-detection_dynamic.py', '../../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(model_inputs=[
+    dict(
+        opt_shapes=dict(
+            voxels=[20000, 64, 4], num_points=[20000], coors=[20000, 4]))
+])

configs/mmdet3d/voxel-detection/voxel-detection_static.py

+_base_ = ['../../_base_/onnx_config.py']
+codebase_config = dict(
+    type='mmdet3d', task='VoxelDetection', model_type='end2end')
+onnx_config = dict(
+    input_names=['voxels', 'num_points', 'coors'],
+    # need to change output_names for head with multi-level features
+    output_names=['cls_score0', 'bbox_pred0', 'dir_cls_pred0'])

configs/mmdet3d/voxel-detection/voxel-detection_tensorrt_dynamic-kitti-32x4.py

+_base_ = ['./voxel-detection_dynamic.py', '../../_base_/backends/tensorrt.py']
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                voxels=dict(
+                    min_shape=[2000, 32, 4],
+                    opt_shape=[5000, 32, 4],
+                    max_shape=[9000, 32, 4]),
+                num_points=dict(
+                    min_shape=[2000], opt_shape=[5000], max_shape=[9000]),
+                coors=dict(
+                    min_shape=[2000, 4],
+                    opt_shape=[5000, 4],
+                    max_shape=[9000, 4]),
+            ))
+    ])

configs/mmdet3d/voxel-detection/voxel-detection_tensorrt_dynamic-nus-20x5.py

+_base_ = ['./voxel-detection_dynamic.py', '../../_base_/backends/tensorrt.py']
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 32),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                voxels=dict(
+                    min_shape=[5000, 20, 5],
+                    opt_shape=[20000, 20, 5],
+                    max_shape=[30000, 20, 5]),
+                num_points=dict(
+                    min_shape=[5000], opt_shape=[20000], max_shape=[30000]),
+                coors=dict(
+                    min_shape=[5000, 4],
+                    opt_shape=[20000, 4],
+                    max_shape=[30000, 4]),
+            ))
+    ])

configs/mmdet3d/voxel-detection/voxel-detection_tensorrt_dynamic-nus-64x4.py

+_base_ = ['./voxel-detection_dynamic.py', '../../_base_/backends/tensorrt.py']
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 32),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                voxels=dict(
+                    min_shape=[5000, 64, 4],
+                    opt_shape=[20000, 64, 4],
+                    max_shape=[30000, 64, 4]),
+                num_points=dict(
+                    min_shape=[5000], opt_shape=[20000], max_shape=[30000]),
+                coors=dict(
+                    min_shape=[5000, 4],
+                    opt_shape=[20000, 4],
+                    max_shape=[30000, 4]),
+            ))
+    ])

configs/mmocr/text-detection/text-detection_ascend_dynamic-640x640-1280x1280.py

+_base_ = ['./text-detection_dynamic.py', '../../_base_/backends/ascend.py']
+
+onnx_config = dict(input_shape=None)
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(input=[-1, 3, -1, -1]),
+        dynamic_dims=[(1, 640, 640), (4, 640, 640), (1, 1280, 1280)])
+])

configs/mmocr/text-detection/text-detection_ascend_static-640x640.py

+_base_ = ['./text-detection_static.py', '../../_base_/backends/ascend.py']
+
+onnx_config = dict(input_shape=[640, 640])
+backend_config = dict(
+    model_inputs=[dict(input_shapes=dict(input=[1, 3, 640, 640]))])

configs/mmocr/text-detection/text-detection_coreml_static-512x512.py

+_base_ = [
+    './text-detection_static.py', '../../_base_/torchscript_config.py',
+    '../../_base_/backends/coreml.py'
+]
+
+ir_config = dict(input_shape=[512, 512])
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 512, 512],
+                max_shape=[1, 3, 512, 512],
+                default_shape=[1, 3, 512, 512])))
+])

configs/mmocr/text-detection/text-detection_dynamic.py

+_base_ = ['./text-detection_static.py']
+onnx_config = dict(
+    dynamic_axes={
+        'input': {
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        },
+        'output': {
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        }
+    }, )

configs/mmocr/text-detection/text-detection_mrcnn_onnxruntime_dynamic.py

+_base_ = ['./text-detection_static.py', '../../_base_/backends/onnxruntime.py']
+onnx_config = dict(
+    output_names=['dets', 'labels', 'masks'],
+    dynamic_axes=dict(
+        input=dict({
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        }),
+        dets=dict({
+            0: 'batch',
+            1: 'num_dets'
+        }),
+        labels=dict({
+            0: 'batch',
+            1: 'num_dets'
+        }),
+        masks=dict({
+            0: 'batch',
+            1: 'num_dets',
+            2: 'height',
+            3: 'width'
+        })))
+codebase_config = dict(
+    post_processing=dict(
+        score_threshold=0.05,
+        confidence_threshold=0.005,
+        iou_threshold=0.5,
+        max_output_boxes_per_class=200,
+        pre_top_k=5000,
+        keep_top_k=100,
+        background_label_id=-1,
+        export_postprocess_mask=False))

configs/mmocr/text-detection/text-detection_mrcnn_tensorrt-fp16_dynamic-320x320-2240x2240.py

+_base_ = ['./text-detection_mrcnn_tensorrt_dynamic-320x320-2240x2240.py']
+backend_config = dict(common_config=dict(fp16_mode=True))

configs/mmocr/text-detection/text-detection_mrcnn_tensorrt-int8_dynamic-320x320-2240x2240.py

+_base_ = ['./text-detection_mrcnn_tensorrt_dynamic-320x320-2240x2240.py']
+
+backend_config = dict(common_config=dict(fp16_mode=True, int8_mode=True))
+
+calib_config = dict(create_calib=True, calib_file='calib_data.h5')

configs/mmocr/text-detection/text-detection_mrcnn_tensorrt_dynamic-320x320-2240x2240.py

+_base_ = ['./text-detection_static.py', '../../_base_/backends/tensorrt.py']
+onnx_config = dict(
+    output_names=['dets', 'labels', 'masks'],
+    dynamic_axes=dict(
+        input=dict({
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        }),
+        dets=dict({
+            0: 'batch',
+            1: 'num_dets'
+        }),
+        labels=dict({
+            0: 'batch',
+            1: 'num_dets'
+        }),
+        masks=dict({
+            0: 'batch',
+            1: 'num_dets',
+            2: 'height',
+            3: 'width'
+        })))
+
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 320, 320],
+                    opt_shape=[1, 3, 600, 800],
+                    max_shape=[1, 3, 2240, 2240])))
+    ])
+
+codebase_config = dict(
+    post_processing=dict(
+        score_threshold=0.05,
+        confidence_threshold=0.005,
+        iou_threshold=0.5,
+        max_output_boxes_per_class=200,
+        pre_top_k=5000,
+        keep_top_k=100,
+        background_label_id=-1,
+        export_postprocess_mask=False))

configs/mmocr/text-detection/text-detection_mrcnn_torchscript.py

+_base_ = [
+    '../../_base_/torchscript_config.py',
+    '../../_base_/backends/torchscript.py'
+]
+
+ir_config = dict(input_shape=None, output_names=['dets', 'labels', 'masks'])
+codebase_config = dict(
+    type='mmocr',
+    task='TextDetection',
+    post_processing=dict(
+        score_threshold=0.05,
+        confidence_threshold=0.005,
+        iou_threshold=0.5,
+        max_output_boxes_per_class=200,
+        pre_top_k=5000,
+        keep_top_k=100,
+        background_label_id=-1,
+        export_postprocess_mask=False))

configs/mmocr/text-detection/text-detection_ncnn-int8_static.py

+_base_ = ['./text-detection_static.py', '../../_base_/backends/ncnn-int8.py']
+
+onnx_config = dict(input_shape=None)