[Fix] Adapt latest mmcv (#253)

* Adapt to the latest mmcv and mmengine

* fixed ut_subnet_sampler_loop

* fix get_model

* fix lints

Co-authored-by: humu789 <humu@pjlab.org.cn>

configs/nas/mmcls/spos/spos_shufflenet_search_8xb128_in1k.py

@@ -0,0 +1,13 @@
+_base_ = ['./spos_shufflenet_supernet_8xb128_in1k.py']
+
+train_cfg = dict(
+    _delete_=True,
+    type='mmrazor.EvolutionSearchLoop',
+    dataloader=_base_.val_dataloader,
+    evaluator=_base_.val_evaluator,
+    max_epochs=2,
+    num_candidates=4,
+    top_k=2,
+    num_mutation=2,
+    num_crossover=2,
+    mutate_prob=0.1)

docs/en/advanced_guides/algorithm.md

@@ -1 +1 @@
-# Algorithm
+# Algorithm

docs/en/advanced_guides/customize_architectures.md

@@ -1 +1 @@
-# Customize Architectures
+# Customize Architectures

docs/en/advanced_guides/customize_kd_algorithms.md

@@ -1 +1 @@
-# Customize KD algorithms
+# Customize KD algorithms

docs/en/advanced_guides/customize_mixed_algorithms.md

@@ -1 +1 @@
-# Customize mixed algorithms
+# Customize mixed algorithms

docs/en/advanced_guides/customize_nas_algorithms.md

@@ -1 +1 @@
-# Customize NAS algorithms
+# Customize NAS algorithms

docs/en/advanced_guides/customize_pruning_algorithms.md

@@ -1 +1 @@
-# Customize pruning algorithms
+# Customize pruning algorithms

docs/en/advanced_guides/delivery.md

@@ -1 +1 @@
-# Delivery
+# Delivery

docs/en/advanced_guides/index.rst

@@ -21,4 +21,4 @@ Development tutorials
    customize_pruning_algorithms.md
    customize_kd_algorithms.md
    customize_mixed_algorithms.md
-   apply_existing_algorithms_to_new_tasks.md
+   apply_existing_algorithms_to_new_tasks.md

docs/en/advanced_guides/mutable.md

@@ -1 +1 @@
-# Mutable
+# Mutable

docs/en/advanced_guides/mutator.md

@@ -1 +1 @@
-# Mutator
+# Mutator

docs/en/advanced_guides/recorder.md

@@ -1 +1 @@
-# Recorder
+# Recorder

docs/en/conf.py

@@ -17,19 +17,20 @@
 
 sys.path.insert(0, os.path.abspath('../..'))
 
-
 # -- Project information -----------------------------------------------------
 
 project = 'mmrazor'
 copyright = '2018-2022, OpenMMLab'
 author = 'MMRazor Author'
 version_file = '../../mmflow/version.py'
 
+
 def get_version():
     with open(version_file, 'r') as f:
         exec(compile(f.read(), version_file, 'exec'))
     return locals()['__version__']
 
+
 # -- General configuration ---------------------------------------------------
 
 # Add any Sphinx extension module names here, as strings. They can be
@@ -96,4 +97,4 @@ def get_version():
 # -- Extension configuration -------------------------------------------------
 # Ignore >>> when copying code
 copybutton_prompt_text = r'>>> |\.\.\. '
-copybutton_prompt_is_regexp = True
+copybutton_prompt_is_regexp = True

docs/en/get_started/installation.md

@@ -1 +1 @@
-# Installation
+# Installation

docs/en/get_started/model_zoo.md

@@ -1 +1 @@
-# Model Zoo
+# Model Zoo

docs/en/make.bat

@@ -1,35 +1,35 @@
-@ECHO OFF
-
-pushd %~dp0
-
-REM Command file for Sphinx documentation
-
-if "%SPHINXBUILD%" == "" (
-	set SPHINXBUILD=sphinx-build
-)
-set SOURCEDIR=.
-set BUILDDIR=_build
-
-if "%1" == "" goto help
-
-%SPHINXBUILD% >NUL 2>NUL
-if errorlevel 9009 (
-	echo.
-	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
-	echo.installed, then set the SPHINXBUILD environment variable to point
-	echo.to the full path of the 'sphinx-build' executable. Alternatively you
-	echo.may add the Sphinx directory to PATH.
-	echo.
-	echo.If you don't have Sphinx installed, grab it from
-	echo.http://sphinx-doc.org/
-	exit /b 1
-)
-
-%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-goto end
-
-:help
-%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
-
-:end
-popd
+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=.
+set BUILDDIR=_build
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.http://sphinx-doc.org/
+	exit /b 1
+)
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd

docs/en/notes/changelog.md

@@ -1 +1 @@
-# Changelog
+# Changelog

docs/en/notes/faq.md

@@ -1 +1 @@
-# Frequently Asked Questions
+# Frequently Asked Questions

docs/en/user_guides/1_learn_about_config.md

@@ -1 +1 @@
-# Learn about Configs
+# Learn about Configs

docs/en/user_guides/2_train_different_types_algorithms.md

@@ -1 +1 @@
-# Train different types algorithms
+# Train different types algorithms

docs/en/user_guides/3_train_with_different_devices.md

@@ -1 +1 @@
-# Train with different devices
+# Train with different devices

docs/en/user_guides/4_test_a_model.md

@@ -1 +1 @@
-# Test a model
+# Test a model

docs/en/user_guides/analysis_tools.md

@@ -1 +1 @@
-# Analysis tools
+# Analysis tools

docs/en/user_guides/index.rst

@@ -28,4 +28,3 @@ Introductions
    nas.md
    pruning.md
    kd.md
-

docs/en/user_guides/kd.md

@@ -1 +1 @@
-# Knowledge Distillation
+# Knowledge Distillation

docs/en/user_guides/nas.md

@@ -1 +1 @@
-# Neural Architecture Search
+# Neural Architecture Search

docs/en/user_guides/pruning.md

@@ -1 +1 @@
-# Pruning
+# Pruning

docs/en/user_guides/visualization.md

@@ -1 +1 @@
-# Visualization
+# Visualization

mmrazor/engine/hooks/estimate_resources_hook.py

@@ -3,9 +3,9 @@
 from typing import Any, Dict, Optional, Sequence
 
 import torch
-from mmengine.data import BaseDataElement
 from mmengine.hooks import Hook
 from mmengine.registry import HOOKS
+from mmengine.structures import BaseDataElement
 
 from mmrazor.models.task_modules import ResourceEstimator
 

mmrazor/models/algorithms/base.py

@@ -3,8 +3,8 @@
 
 import torch
 import torch.nn as nn
-from mmengine import BaseDataElement
 from mmengine.model import BaseModel
+from mmengine.structures import BaseDataElement
 
 from mmrazor.registry import MODELS
 
@@ -80,7 +80,7 @@ def __init__(self,
         self.architecture = architecture
 
     def forward(self,
-                batch_inputs: torch.Tensor,
+                inputs: torch.Tensor,
                 data_samples: Optional[List[BaseDataElement]] = None,
                 mode: str = 'tensor') -> ForwardResults:
         """Returns losses or predictions of training, validation, testing, and
@@ -129,36 +129,36 @@ def forward(self,
                   or ``dict of tensor for custom use.
         """
         if mode == 'loss':
-            return self.loss(batch_inputs, data_samples)
+            return self.loss(inputs, data_samples)
         elif mode == 'tensor':
-            return self._forward(batch_inputs, data_samples)
+            return self._forward(inputs, data_samples)
         elif mode == 'predict':
-            return self._predict(batch_inputs, data_samples)
+            return self._predict(inputs, data_samples)
         else:
             raise RuntimeError(f'Invalid mode "{mode}". '
                                'Only supports loss, predict and tensor mode')
 
     def loss(
         self,
-        batch_inputs: torch.Tensor,
+        inputs: torch.Tensor,
         data_samples: Optional[List[BaseDataElement]] = None,
     ) -> LossResults:
         """Calculate losses from a batch of inputs and data samples."""
-        return self.architecture(batch_inputs, data_samples, mode='loss')
+        return self.architecture(inputs, data_samples, mode='loss')
 
     def _forward(
         self,
-        batch_inputs: torch.Tensor,
+        inputs: torch.Tensor,
         data_samples: Optional[List[BaseDataElement]] = None,
     ) -> TensorResults:
         """Network forward process."""
-        return self.architecture(batch_inputs, data_samples, mode='tensor')
+        return self.architecture(inputs, data_samples, mode='tensor')
 
     def _predict(
         self,
-        batch_inputs: torch.Tensor,
+        inputs: torch.Tensor,
         data_samples: Optional[List[BaseDataElement]] = None,
     ) -> PredictResults:
         """Predict results from a batch of inputs and data samples with post-
         processing."""
-        return self.architecture(batch_inputs, data_samples, mode='predict')
+        return self.architecture(inputs, data_samples, mode='predict')

mmrazor/models/algorithms/distill/configurable/datafree_distillation.py

@@ -154,13 +154,14 @@ def train_generator(
         fakeimg = self.generator(fakeimg_init, batch_size)
 
         with optimizer.optim_context(self.generator):
-            _, data_samples = self.data_preprocessor(data, True)
+            pseudo_data = self.data_preprocessor(data, True)
+            pseudo_data_samples = pseudo_data['data_samples']
             # recorde the needed information
             with self.generator_distiller.student_recorders:
-                _ = self.student(fakeimg, data_samples, mode='loss')
+                _ = self.student(fakeimg, pseudo_data_samples, mode='loss')
             with self.generator_distiller.teacher_recorders:
                 for _, teacher in self.teachers.items():
-                    _ = teacher(fakeimg, data_samples, mode='loss')
+                    _ = teacher(fakeimg, pseudo_data_samples, mode='loss')
             loss_generator = self.generator_distiller.compute_distill_losses()
 
         generator_loss, generator_loss_vars = self.parse_losses(loss_generator)
@@ -192,15 +193,16 @@ def train_step(self, data: List[dict],
         fakeimg_init = torch.randn(
             (batch_size, self.generator.module.latent_dim))
         fakeimg = self.generator(fakeimg_init, batch_size)
-        _, data_samples = self.data_preprocessor(data, True)
+        pseudo_data = self.data_preprocessor(data, True)
+        pseudo_data_samples = pseudo_data['data_samples']
 
         with optim_wrapper['generator'].optim_context(self.generator):
             # recorde the needed information
             with self.generator_distiller.student_recorders:
-                _ = self.student(fakeimg, data_samples, mode='loss')
+                _ = self.student(fakeimg, pseudo_data_samples, mode='loss')
             with self.generator_distiller.teacher_recorders:
                 for _, teacher in self.teachers.items():
-                    _ = teacher(fakeimg, data_samples, mode='loss')
+                    _ = teacher(fakeimg, pseudo_data_samples, mode='loss')
             loss_generator = self.generator_distiller.compute_distill_losses()
 
         generator_loss, generator_loss_vars = self.parse_losses(loss_generator)
@@ -209,10 +211,12 @@ def train_step(self, data: List[dict],
         with optim_wrapper['architecture'].optim_context(self.student):
             # recorde the needed information
             with self.distiller.student_recorders:
-                _ = self.student(fakeimg.detach(), data_samples, mode='loss')
+                _ = self.student(
+                    fakeimg.detach(), pseudo_data_samples, mode='loss')
             with self.distiller.teacher_recorders, torch.no_grad():
                 for _, teacher in self.teachers.items():
-                    _ = teacher(fakeimg.detach(), data_samples, mode='loss')
+                    _ = teacher(
+                        fakeimg.detach(), pseudo_data_samples, mode='loss')
             loss_distill = self.distiller.compute_distill_losses()
 
         distill_loss, distill_log_vars = self.parse_losses(loss_distill)

mmrazor/models/algorithms/distill/configurable/fpn_teacher_distill.py

@@ -2,7 +2,7 @@
 from typing import List, Optional
 
 import torch
-from mmengine import BaseDataElement
+from mmengine.structures import BaseDataElement
 
 from mmrazor.models.utils import add_prefix
 from mmrazor.registry import MODELS

mmrazor/models/algorithms/distill/configurable/self_distill.py

@@ -2,7 +2,7 @@
 from typing import List, Optional
 
 import torch
-from mmengine import BaseDataElement
+from mmengine.structures import BaseDataElement
 from torch import nn
 
 from mmrazor.models.utils import add_prefix

mmrazor/models/algorithms/distill/configurable/single_teacher_distill.py

@@ -2,9 +2,9 @@
 from typing import Dict, List, Optional, Union
 
 import torch
-from mmengine import BaseDataElement
 from mmengine.model import BaseModel
 from mmengine.runner import load_checkpoint
+from mmengine.structures import BaseDataElement
 from torch import nn
 from torch.nn.modules.batchnorm import _BatchNorm
 

mmrazor/models/algorithms/nas/autoslim.py

@@ -4,9 +4,9 @@
 from typing import Dict, List, Optional, Union
 
 import torch
-from mmengine import BaseDataElement
 from mmengine.model import BaseModel, MMDistributedDataParallel
 from mmengine.optim import OptimWrapper
+from mmengine.structures import BaseDataElement
 from torch import nn
 
 from mmrazor.models.distillers import ConfigurableDistiller

mmrazor/models/algorithms/nas/spos.py

@@ -2,8 +2,8 @@
 from typing import Dict, List, Optional, Union
 
 import torch
-from mmengine import BaseDataElement
 from mmengine.model import BaseModel
+from mmengine.structures import BaseDataElement
 from torch import nn
 from torch.nn.modules.batchnorm import _BatchNorm