add config module

configs/mmpretrain/classification_ascend_dynamic-224x224-224x224.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/ascend.py']
+
+onnx_config = dict(input_shape=[224, 224])
+
+backend_config = dict(model_inputs=[
+    dict(
+        dynamic_batch_size=[1, 2, 4, 8],
+        input_shapes=dict(input=[-1, 3, 224, 224]))
+])

configs/mmpretrain/classification_ascend_static-224x224.py

+_base_ = ['./classification_static.py', '../_base_/backends/ascend.py']
+
+onnx_config = dict(input_shape=[224, 224])
+backend_config = dict(
+    model_inputs=[dict(input_shapes=dict(input=[1, 3, 224, 224]))])

configs/mmpretrain/classification_coreml_dynamic-224x224-224x224.py

+_base_ = ['../_base_/torchscript_config.py', '../_base_/backends/coreml.py']
+
+codebase_config = dict(type='mmpretrain', task='Classification')
+
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 224, 224],
+                max_shape=[8, 3, 224, 224],
+                default_shape=[1, 3, 224, 224])))
+])

configs/mmpretrain/classification_dynamic.py

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

configs/mmpretrain/classification_ncnn-int8_static.py

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

configs/mmpretrain/classification_ncnn_dynamic.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/ncnn.py']

configs/mmpretrain/classification_ncnn_static.py

+_base_ = ['./classification_static.py', '../_base_/backends/ncnn.py']
+
+onnx_config = dict(input_shape=None)

configs/mmpretrain/classification_onnxruntime-fp16_dynamic.py

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

configs/mmpretrain/classification_onnxruntime_dynamic.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/onnxruntime.py']

configs/mmpretrain/classification_onnxruntime_static.py

+_base_ = ['./classification_static.py', '../_base_/backends/onnxruntime.py']
+
+onnx_config = dict(input_shape=None)

configs/mmpretrain/classification_openvino_dynamic-224x224.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/openvino.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(
+    model_inputs=[dict(opt_shapes=dict(input=[1, 3, 224, 224]))])

configs/mmpretrain/classification_pplnn_dynamic-224x224.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/pplnn.py']
+
+onnx_config = dict(input_shape=None)
+
+backend_config = dict(model_inputs=dict(opt_shape=[1, 3, 224, 224]))

configs/mmpretrain/classification_rknn-fp16_static-224x224.py

+_base_ = ['./classification_static.py', '../_base_/backends/rknn.py']
+
+onnx_config = dict(input_shape=[224, 224])
+codebase_config = dict(model_type='end2end')
+backend_config = dict(
+    input_size_list=[[3, 224, 224]],
+    quantization_config=dict(do_quantization=False))

configs/mmpretrain/classification_rknn-int8_static-224x224.py

+_base_ = ['./classification_static.py', '../_base_/backends/rknn.py']
+
+onnx_config = dict(input_shape=[224, 224])
+codebase_config = dict(model_type='end2end')
+backend_config = dict(input_size_list=[[3, 224, 224]])

configs/mmpretrain/classification_sdk_dynamic.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/sdk.py']
+
+codebase_config = dict(model_type='sdk')
+
+backend_config = dict(
+    pipeline=[dict(type='LoadImageFromFile'),
+              dict(type='PackInputs')])

configs/mmpretrain/classification_snpe_static.py

+_base_ = ['./classification_static.py', '../_base_/backends/snpe.py']
+
+onnx_config = dict(input_shape=None)

configs/mmpretrain/classification_static.py

+_base_ = ['../_base_/onnx_config.py']
+
+codebase_config = dict(type='mmpretrain', task='Classification')

configs/mmpretrain/classification_tensorrt-fp16_dynamic-224x224-224x224.py

+_base_ = ['./classification_dynamic.py', '../_base_/backends/tensorrt-fp16.py']
+
+onnx_config = dict(input_shape=[224, 224])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 224, 224],
+                    opt_shape=[4, 3, 224, 224],
+                    max_shape=[8, 3, 224, 224])))
+    ])

configs/mmpretrain/classification_tensorrt-fp16_static-224x224.py

+_base_ = ['./classification_static.py', '../_base_/backends/tensorrt-fp16.py']
+
+onnx_config = dict(input_shape=[224, 224])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 224, 224],
+                    opt_shape=[1, 3, 224, 224],
+                    max_shape=[1, 3, 224, 224])))
+    ])

configs/mmpretrain/classification_tensorrt-fp16_static-384x384.py

+_base_ = ['./classification_static.py', '../_base_/backends/tensorrt-fp16.py']
+
+onnx_config = dict(input_shape=[384, 384])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 384, 384],
+                    opt_shape=[1, 3, 384, 384],
+                    max_shape=[1, 3, 384, 384])))
+    ])