add config module

configs/mmagic/super-resolution/super-resolution_tensorrt_static-256x256.py

+_base_ = ['./super-resolution_static.py', '../../_base_/backends/tensorrt.py']
+onnx_config = dict(input_shape=[256, 256])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 256, 256],
+                    opt_shape=[1, 3, 256, 256],
+                    max_shape=[1, 3, 256, 256])))
+    ])

configs/mmagic/super-resolution/super-resolution_torchscript.py

+_base_ = [
+    '../../_base_/torchscript_config.py',
+    '../../_base_/backends/torchscript.py'
+]
+
+ir_config = dict(input_shape=None)
+codebase_config = dict(type='mmagic', task='SuperResolution')

configs/mmdet/_base_/base_coreml_static-800x1344.py

+_base_ = ['./base_torchscript.py', '../../_base_/backends/coreml.py']
+
+ir_config = dict(input_shape=(1344, 800))
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 800, 1344],
+                max_shape=[1, 3, 800, 1344],
+                default_shape=[1, 3, 800, 1344])))
+])

configs/mmdet/_base_/base_dynamic.py

+_base_ = ['./base_static.py']
+onnx_config = dict(
+    dynamic_axes={
+        'input': {
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        },
+        'dets': {
+            0: 'batch',
+            1: 'num_dets',
+        },
+        'labels': {
+            0: 'batch',
+            1: 'num_dets',
+        },
+    }, )

configs/mmdet/_base_/base_instance-seg_dynamic.py

+_base_ = ['./base_instance-seg_static.py']
+onnx_config = dict(
+    dynamic_axes={
+        'input': {
+            0: 'batch',
+            2: 'height',
+            3: 'width'
+        },
+        'dets': {
+            0: 'batch',
+            1: 'num_dets',
+        },
+        'labels': {
+            0: 'batch',
+            1: 'num_dets',
+        },
+        'masks': {
+            0: 'batch',
+            1: 'num_dets',
+            2: 'height',
+            3: 'width'
+        },
+    })

configs/mmdet/_base_/base_instance-seg_static.py

+_base_ = ['./base_static.py']
+
+onnx_config = dict(output_names=['dets', 'labels', 'masks'])
+codebase_config = dict(post_processing=dict(export_postprocess_mask=False))

configs/mmdet/_base_/base_instance-seg_torchscript.py

+_base_ = ['./base_torchscript.py']
+
+ir_config = dict(output_names=['dets', 'labels', 'masks'])
+codebase_config = dict(post_processing=dict(export_postprocess_mask=False))

configs/mmdet/_base_/base_openvino_dynamic-300x300.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(
+    model_inputs=[dict(opt_shapes=dict(input=[1, 3, 300, 300]))])

configs/mmdet/_base_/base_openvino_dynamic-640x640.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(
+    model_inputs=[dict(opt_shapes=dict(input=[1, 3, 640, 640]))])

configs/mmdet/_base_/base_openvino_dynamic-800x1344.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(
+    model_inputs=[dict(opt_shapes=dict(input=[1, 3, 800, 1344]))])

configs/mmdet/_base_/base_panoptic-seg_static.py

+_base_ = ['../../_base_/onnx_config.py']
+
+codebase_config = dict(
+    type='mmdet',
+    task='ObjectDetection',
+    model_type='panoptic_end2end',
+    post_processing=dict(
+        export_postprocess_mask=False,
+        score_threshold=0.0,
+        iou_threshold=0.5,
+        max_output_boxes_per_class=200,
+        pre_top_k=5000,
+        keep_top_k=100,
+        background_label_id=-1,
+    ))

configs/mmdet/_base_/base_static.py

+_base_ = ['../../_base_/onnx_config.py']
+
+onnx_config = dict(output_names=['dets', 'labels'], input_shape=None)
+codebase_config = dict(
+    type='mmdet',
+    task='ObjectDetection',
+    model_type='end2end',
+    post_processing=dict(
+        score_threshold=0.05,
+        confidence_threshold=0.005,  # for YOLOv3
+        iou_threshold=0.5,
+        max_output_boxes_per_class=200,
+        pre_top_k=5000,
+        keep_top_k=100,
+        background_label_id=-1,
+    ))

configs/mmdet/_base_/base_tensorrt-fp16_dynamic-300x300-512x512.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/tensorrt-fp16.py']
+
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 300, 300],
+                    opt_shape=[1, 3, 300, 300],
+                    max_shape=[1, 3, 512, 512])))
+    ])

configs/mmdet/_base_/base_tensorrt-fp16_dynamic-320x320-1344x1344.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/tensorrt-fp16.py']
+
+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, 800, 1344],
+                    max_shape=[1, 3, 1344, 1344])))
+    ])

configs/mmdet/_base_/base_tensorrt-fp16_static-800x1344.py

+_base_ = ['./base_static.py', '../../_base_/backends/tensorrt-fp16.py']
+
+onnx_config = dict(input_shape=(1344, 800))
+
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 800, 1344],
+                    opt_shape=[1, 3, 800, 1344],
+                    max_shape=[1, 3, 800, 1344])))
+    ])

configs/mmdet/_base_/base_tensorrt-int8_dynamic-300x300-512x512.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/tensorrt-int8.py']
+
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 300, 300],
+                    opt_shape=[1, 3, 300, 300],
+                    max_shape=[1, 3, 512, 512])))
+    ])

configs/mmdet/_base_/base_tensorrt-int8_dynamic-320x320-1344x1344.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/tensorrt-int8.py']
+
+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, 800, 1344],
+                    max_shape=[1, 3, 1344, 1344])))
+    ])

configs/mmdet/_base_/base_tensorrt-int8_static-800x1344.py

+_base_ = ['./base_static.py', '../../_base_/backends/tensorrt-int8.py']
+
+onnx_config = dict(input_shape=(1344, 800))
+
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 800, 1344],
+                    opt_shape=[1, 3, 800, 1344],
+                    max_shape=[1, 3, 800, 1344])))
+    ])

configs/mmdet/_base_/base_tensorrt_dynamic-300x300-512x512.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/tensorrt.py']
+
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 300, 300],
+                    opt_shape=[1, 3, 300, 300],
+                    max_shape=[1, 3, 512, 512])))
+    ])

configs/mmdet/_base_/base_tensorrt_dynamic-320x320-1344x1344.py

+_base_ = ['./base_dynamic.py', '../../_base_/backends/tensorrt.py']
+
+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, 800, 1344],
+                    max_shape=[1, 3, 1344, 1344])))
+    ])