Add tensorrt int8 and fp16 configs for all the rest codebases (#152)

* add configs for all codebases except mmocr and fixed some bugs

* add ocr det

* add fp16 and int8 config for text recog

configs/_base_/backends/tensorrt_fp16.py

@@ -0,0 +1,6 @@
+import tensorrt as trt
+
+backend_config = dict(
+    type='tensorrt',
+    common_config=dict(
+        fp16_mode=True, log_level=trt.Logger.INFO, max_workspace_size=0))

configs/mmcls/classification_tensorrt_fp16_dynamic-224x224-224x224.py

@@ -0,0 +1,13 @@
+_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=[64, 3, 224, 224])))
+    ])

configs/mmcls/classification_tensorrt_fp16_static-224x224.py

@@ -0,0 +1,13 @@
+_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/mmdet/_base_/base_tensorrt_fp16_dynamic-320x320-1344x1344.py

@@ -0,0 +1,12 @@
+_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

@@ -0,0 +1,14 @@
+_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/single-stage/single-stage_tensorrt_fp16_dynamic-320x320-1344x1344.py

@@ -0,0 +1 @@
+_base_ = ['../_base_/base_tensorrt_fp16_dynamic-320x320-1344x1344.py']

configs/mmdet/single-stage/single-stage_tensorrt_fp16_static-800x1344.py

@@ -0,0 +1 @@
+_base_ = ['../_base_/base_tensorrt_fp16_static-800x1344.py']

configs/mmdet/two-stage/two-stage_partition_tensorrt-fp16_dynamic-320x320-1344x1344.py

@@ -0,0 +1,19 @@
+_base_ = ['./two-stage_tensorrt_fp16_dynamic-320x320-1344x1344.py']
+
+partition_config = dict(type='two_stage', apply_marks=True)
+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]))),
+        dict(
+            input_shapes=dict(
+                bbox_feats=dict(
+                    min_shape=[500, 256, 7, 7],
+                    opt_shape=[1000, 256, 7, 7],
+                    max_shape=[2000, 256, 7, 7])))
+    ])

configs/mmdet/two-stage/two-stage_tensorrt_fp16_dynamic-320x320-1344x1344.py

@@ -0,0 +1 @@
+_base_ = ['../_base_/base_tensorrt_fp16_dynamic-320x320-1344x1344.py']

configs/mmdet/two-stage/two-stage_tensorrt_fp16_static-800x1344.py

@@ -0,0 +1 @@
+_base_ = ['../_base_/base_tensorrt_fp16_static-800x1344.py']

configs/mmdet/with-mask/mask_tensorrt_fp16_dynamic-320x320-1344x1344.py

@@ -0,0 +1,14 @@
+_base_ = [
+    '../_base_/mask_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/with-mask/mask_tensorrt_fp16_static-800x1344.py

@@ -0,0 +1,15 @@
+_base_ = [
+    '../_base_/mask_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/with-mask/mask_tensorrt_int8_dynamic-320x320-1344x1344.py

@@ -0,0 +1,14 @@
+_base_ = [
+    '../_base_/mask_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/with-mask/mask_tensorrt_int8_static-800x1344.py

@@ -0,0 +1,15 @@
+_base_ = [
+    '../_base_/mask_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/mmedit/super-resolution/super-resolution_tensorrt_fp16_dynamic-32x32-512x512.py

@@ -0,0 +1,11 @@
+_base_ = [
+    './super-resolution_dynamic.py', '../../_base_/backends/tensorrt_fp16.py'
+]
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 32, 32],
+                opt_shape=[1, 3, 256, 256],
+                max_shape=[1, 3, 512, 512])))
+])

configs/mmedit/super-resolution/super-resolution_tensorrt_fp16_static-256x256.py

@@ -0,0 +1,12 @@
+_base_ = [
+    './super-resolution_static.py', '../../_base_/backends/tensorrt_fp16.py'
+]
+onnx_config = dict(input_shape=[256, 256])
+backend_config = dict(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/mmedit/super-resolution/super-resolution_tensorrt_int8_dynamic-32x32-512x512.py

@@ -0,0 +1,11 @@
+_base_ = [
+    './super-resolution_dynamic.py', '../../_base_/backends/tensorrt_int8.py'
+]
+backend_config = dict(model_inputs=[
+    dict(
+        input_shapes=dict(
+            input=dict(
+                min_shape=[1, 3, 32, 32],
+                opt_shape=[1, 3, 256, 256],
+                max_shape=[1, 3, 512, 512])))
+])

configs/mmedit/super-resolution/super-resolution_tensorrt_int8_static-256x256.py

@@ -0,0 +1,12 @@
+_base_ = [
+    './super-resolution_static.py', '../../_base_/backends/tensorrt_int8.py'
+]
+onnx_config = dict(input_shape=[256, 256])
+backend_config = dict(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/mmocr/text-detection/text-detection_tensorrt_fp16_dynamic-320x320-1024x1824.py

@@ -0,0 +1,13 @@
+_base_ = [
+    './text-detection_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, 600, 800],
+                    max_shape=[1, 3, 1024, 1824])))
+    ])

configs/mmocr/text-detection/text-detection_tensorrt_fp16_static-512x512.py

@@ -0,0 +1,15 @@
+_base_ = [
+    './text-detection_static.py', '../../_base_/backends/tensorrt_fp16.py'
+]
+
+onnx_config = dict(input_shape=[512, 512])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 512, 512],
+                    opt_shape=[1, 3, 512, 512],
+                    max_shape=[1, 3, 512, 512])))
+    ])

configs/mmocr/text-detection/text-detection_tensorrt_int8_dynamic-320x320-1024x1824.py

@@ -0,0 +1,13 @@
+_base_ = [
+    './text-detection_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, 600, 800],
+                    max_shape=[1, 3, 1024, 1824])))
+    ])

configs/mmocr/text-detection/text-detection_tensorrt_int8_static-512x512.py

@@ -0,0 +1,15 @@
+_base_ = [
+    './text-detection_static.py', '../../_base_/backends/tensorrt_int8.py'
+]
+
+onnx_config = dict(input_shape=[512, 512])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 512, 512],
+                    opt_shape=[1, 3, 512, 512],
+                    max_shape=[1, 3, 512, 512])))
+    ])

configs/mmocr/text-recognition/text-recognition_tensorrt_fp16_dynamic-1x32x32-1x32x640.py

@@ -0,0 +1,13 @@
+_base_ = [
+    './text-recognition_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, 1, 32, 32],
+                    opt_shape=[1, 1, 32, 64],
+                    max_shape=[1, 1, 32, 640])))
+    ])

configs/mmocr/text-recognition/text-recognition_tensorrt_fp16_static-1x32x32.py

@@ -0,0 +1,15 @@
+_base_ = [
+    './text-recognition_static.py', '../../_base_/backends/tensorrt_fp16.py'
+]
+
+onnx_config = dict(input_shape=[32, 32])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 1, 32, 32],
+                    opt_shape=[1, 1, 32, 32],
+                    max_shape=[1, 1, 32, 32])))
+    ])

configs/mmocr/text-recognition/text-recognition_tensorrt_int8_dynamic-1x32x32-1x32x640.py

@@ -0,0 +1,13 @@
+_base_ = [
+    './text-recognition_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, 1, 32, 32],
+                    opt_shape=[1, 1, 32, 64],
+                    max_shape=[1, 1, 32, 640])))
+    ])

configs/mmocr/text-recognition/text-recognition_tensorrt_int8_static-1x32x32.py

@@ -0,0 +1,15 @@
+_base_ = [
+    './text-recognition_static.py', '../../_base_/backends/tensorrt_int8.py'
+]
+
+onnx_config = dict(input_shape=[32, 32])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 1, 32, 32],
+                    opt_shape=[1, 1, 32, 32],
+                    max_shape=[1, 1, 32, 32])))
+    ])

configs/mmseg/segmentation_tensorrt_fp16_dynamic-512x1024-2048x2048.py

@@ -0,0 +1,11 @@
+_base_ = ['./segmentation_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, 512, 1024],
+                    opt_shape=[1, 3, 1024, 2048],
+                    max_shape=[1, 3, 2048, 2048])))
+    ])

configs/mmseg/segmentation_tensorrt_fp16_static-512x1024.py

@@ -0,0 +1,13 @@
+_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt_fp16.py']
+
+onnx_config = dict(input_shape=[1024, 512])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 512, 1024],
+                    opt_shape=[1, 3, 512, 1024],
+                    max_shape=[1, 3, 512, 1024])))
+    ])

configs/mmseg/segmentation_tensorrt_int8_dynamic-512x1024-2048x2048.py

@@ -0,0 +1,11 @@
+_base_ = ['./segmentation_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, 512, 1024],
+                    opt_shape=[1, 3, 1024, 2048],
+                    max_shape=[1, 3, 2048, 2048])))
+    ])

configs/mmseg/segmentation_tensorrt_int8_static-512x1024.py

@@ -0,0 +1,13 @@
+_base_ = ['./segmentation_static.py', '../_base_/backends/tensorrt_int8.py']
+
+onnx_config = dict(input_shape=[1024, 512])
+backend_config = dict(
+    common_config=dict(max_workspace_size=1 << 30),
+    model_inputs=[
+        dict(
+            input_shapes=dict(
+                input=dict(
+                    min_shape=[1, 3, 512, 1024],
+                    opt_shape=[1, 3, 512, 1024],
+                    max_shape=[1, 3, 512, 1024])))
+    ])

mmdeploy/apis/utils.py

@@ -359,5 +359,9 @@ def get_tensor_from_input(codebase: Codebase, input_data: Dict[str, Any]):
         from mmdeploy.mmocr.export import get_tensor_from_input \
             as get_tensor_from_input_mmocr
         return get_tensor_from_input_mmocr(input_data)
+    elif codebase == Codebase.MMEDIT:
+        from mmdeploy.mmedit.export import get_tensor_from_input \
+            as get_tensor_from_input_mmedit
+        return get_tensor_from_input_mmedit(input_data)
     else:
         raise NotImplementedError(f'Unknown codebase type: {codebase.value}')

mmdeploy/mmdet/models/roi_heads/test_mixins.py

@@ -45,9 +45,11 @@ def simple_test_mask_of_mask_test_mixin(ctx, self, x, img_metas, det_bboxes,
         bboxes_shape, labels_shape = list(det_bboxes.shape), list(
             det_labels.shape)
         bboxes_shape[1], labels_shape[1] = 1, 1
-        det_bboxes = torch.tensor([[[0., 0., 1., 1.,
+        det_bboxes = torch.tensor(
-                                     0.]]]).expand(*bboxes_shape)
+            [[[0., 0., 1., 1., 0.]]],
-        det_labels = torch.tensor([[0]]).expand(*labels_shape)
+            device=det_bboxes.device).expand(*bboxes_shape)
+        det_labels = torch.tensor(
+            [[0]], device=det_bboxes.device).expand(*labels_shape)
 
     batch_size = det_bboxes.size(0)
     det_bboxes = det_bboxes[..., :4]

mmdeploy/mmedit/export/__init__.py

@@ -1,3 +1,7 @@
-from .prepare_input import build_dataloader, build_dataset, create_input
+from .prepare_input import (build_dataloader, build_dataset, create_input,
+                            get_tensor_from_input)
 
-__all__ = ['create_input', 'build_dataset', 'build_dataloader']
+__all__ = [
+    'create_input', 'build_dataset', 'build_dataloader',
+    'get_tensor_from_input'
+]

mmdeploy/mmedit/export/prepare_input.py

@@ -1,4 +1,4 @@
-from typing import Optional, Sequence, Union
+from typing import Any, Dict, Optional, Sequence, Union
 
 import mmcv
 import numpy as np
@@ -188,3 +188,14 @@ def build_dataloader(dataset: Dataset,
     return build_dataloader_mmedit(dataset, samples_per_gpu, workers_per_gpu,
                                    num_gpus, dist, shuffle, seed, drop_last,
                                    pin_memory, persistent_workers, **kwargs)
+
+
+def get_tensor_from_input(input_data: Dict[str, Any]):
+    """Get input tensor from input data.
+
+    Args:
+        input_data (dict): Input data containing meta info and image tensor.
+    Returns:
+        torch.Tensor: An image in `Tensor`.
+    """
+    return input_data['lq']

mmdeploy/mmocr/export/__init__.py

@@ -1,3 +1,7 @@
-from .prepare_input import build_dataloader, build_dataset, create_input
+from .prepare_input import (build_dataloader, build_dataset, create_input,
+                            get_tensor_from_input)
 
-__all__ = ['create_input', 'build_dataset', 'build_dataloader']
+__all__ = [
+    'create_input', 'build_dataset', 'build_dataloader',
+    'get_tensor_from_input'
+]

mmdeploy/mmocr/export/prepare_input.py

@@ -2,7 +2,7 @@ from typing import Any, Optional, Sequence, Union
 
 import mmcv
 import numpy as np
-from mmcv.parallel import collate, scatter
+from mmcv.parallel import DataContainer, collate, scatter
 from mmdet.datasets import replace_ImageToTensor
 from mmocr.datasets import build_dataloader as build_dataloader_mmocr
 from mmocr.datasets import build_dataset as build_dataset_mmocr
@@ -189,4 +189,6 @@ def get_tensor_from_input(input_data: tuple):
     Returns:
         torch.Tensor: An image in `Tensor`.
     """
-    return input_data['img']
+    if isinstance(input_data['img'], DataContainer):
+        return input_data['img'].data[0]
+    return input_data['img'][0]

mmdeploy/mmseg/export/prepare_input.py

@@ -138,4 +138,4 @@ def get_tensor_from_input(input_data: tuple):
     Returns:
         torch.Tensor: An image in `Tensor`.
     """
-    return input_data['img']
+    return input_data['img'][0]

mmdeploy/mmseg/models/segmentors/base.py

@@ -10,7 +10,11 @@ def forward_of_base_segmentor(ctx, self, img, img_metas=None, **kwargs):
     """Rewrite `forward` for default backend."""
     if img_metas is None:
         img_metas = {}
-    assert isinstance(img_metas, dict)
+    while isinstance(img_metas, list):
+        img_metas = img_metas[0]
+
+    if isinstance(img, list):
+        img = torch.cat(img, 0)
     assert isinstance(img, torch.Tensor)
 
     deploy_cfg = ctx.cfg