Version bump to 3.4.0 (#1613)

* Version bump

* Disable multi gpu

* Postpone removal of some classes in 3.5

Makefile

@@ -39,6 +39,7 @@ NOTEBOOKS_TO_RUN += notebooks/how_to_use_knowledge_distillation_for_classificati
 
 # If there are additional notebooks that must not be executed, but still should be checked for version match, add them here
 NOTEBOOKS_TO_CHECK := $(NOTEBOOKS_TO_RUN)
+NOTEBOOKS_TO_CHECK += notebooks/yolo_nas_pose_eval_with_pycocotools.ipynb
 
 # This Makefile target runs notebooks listed below and converts them to markdown files in documentation/source/
 run_and_convert_notebooks_to_docs: $(NOTEBOOKS_TO_RUN)

documentation/source/models_export.md

@@ -30,13 +30,9 @@ A new export API is introduced in SG 3.2.0. It is aimed to simplify the export p
 
 
 ```python
-!pip install super_gradients==3.3.1
+!pip install -qq super_gradients==3.4.0
 ```
 
-    ERROR: Could not find a version that satisfies the requirement super_gradients==3.3.1 (from versions: 1.3.0, 1.3.1, 1.4.0, 1.5.0, 1.5.1, 1.5.2, 1.6.0, 1.7.1, 1.7.2, 1.7.3, 1.7.4, 1.7.5, 2.0.0, 2.0.1, 2.1.0, 2.2.0, 2.5.0, 2.6.0, 3.0.0, 3.0.1, 3.0.2, 3.0.3, 3.0.4, 3.0.5, 3.0.6, 3.0.7, 3.0.8, 3.0.9, 3.1.0, 3.1.1, 3.1.2, 3.1.3, 3.2.0, 3.2.1, 3.3.0)
-    ERROR: No matching distribution found for super_gradients==3.3.1
-
-
 ### Minimalistic export example
 
 Let start with the most simple example of exporting a model to ONNX format.
@@ -531,7 +527,7 @@ result = session.run(outputs, {inputs[0]: image_bchw})
 show_predictions_from_flat_format(image, result)
 ```
 
-     25%|██████████████████████████████▊                                                                                            | 4/16 [00:11<00:33,  2.79s/it]
+     25%|█████████████████████████████████                                                                                                   | 4/16 [00:11<00:34,  2.91s/it]
 
 
 

documentation/source/models_export_pose.md

@@ -40,7 +40,7 @@ We recommend to use the latest version of TensorRT available.
 
 
 ```python
-!pip install -qq super-gradients==3.3.1
+!pip install -qq super-gradients==3.4.0
 ```
 
 ### Minimalistic export example
@@ -630,7 +630,7 @@ result = session.run(outputs, {inputs[0]: image_bchw})
 show_predictions_from_flat_format(image, result)
 ```
 
-     25%|█████████████████████████████████                                                                                                   | 4/16 [00:12<00:37,  3.15s/it]
+     25%|█████████████████████████████████                                                                                                   | 4/16 [00:12<00:37,  3.10s/it]
 
 
 

notebooks/how_to_use_knowledge_distillation_for_classification.ipynb

@@ -34,7 +34,7 @@
    },
    "outputs": [],
    "source": [
-    "!pip install -qq super_gradients==3.3.1"
+    "!pip install -qq super_gradients==3.4.0"
    ]
   },
   {

notebooks/transfer_learning_classification.ipynb

@@ -59,7 +59,7 @@
     }
    ],
    "source": [
-    "! pip install -qq super-gradients==3.3.1"
+    "! pip install -qq super-gradients==3.4.0"
    ]
   },
   {

notebooks/what_are_recipes_and_how_to_use.ipynb

@@ -41,7 +41,7 @@
   {
    "cell_type": "code",
    "source": [
-    "!pip install -q super-gradients==3.3.1"
+    "!pip install -q super-gradients==3.4.0"
    ],
    "metadata": {
     "id": "8uZM-4va5Rpu",

notebooks/yolo_nas_pose_eval_with_pycocotools.ipynb

@@ -31,6 +31,18 @@
    },
    "id": "f36fcd2e6daa861c"
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!pip install -qq super_gradients==3.4.0"
+   ],
+   "metadata": {
+    "collapsed": false
+   },
+   "id": "319deb6e3293a2c9"
+  },
   {
    "cell_type": "markdown",
    "source": [

src/super_gradients/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "3.3.1"
+__version__ = "3.4.0"
 
 from super_gradients.common import init_trainer, is_distributed, object_names
 from super_gradients.training import losses, utils, datasets_utils, DataAugmentation, Trainer, KDTrainer, QATTrainer

src/super_gradients/examples/model_export/models_export.ipynb

@@ -49,7 +49,7 @@
    "execution_count": null,
    "outputs": [],
    "source": [
-    "!pip install super_gradients==3.3.1"
+    "!pip install -qq super_gradients==3.4.0"
    ],
    "metadata": {
     "collapsed": false

src/super_gradients/examples/model_export/models_export_pose.ipynb

@@ -58,7 +58,7 @@
    "execution_count": 24,
    "outputs": [],
    "source": [
-    "!pip install -qq super-gradients==3.3.1"
+    "!pip install -qq super-gradients==3.4.0"
    ],
    "metadata": {
     "collapsed": false,

src/super_gradients/training/models/__init__.py

@@ -135,7 +135,7 @@
 from super_gradients.training.utils import make_divisible as _make_divisible_current_version, HpmStruct as CurrVersionHpmStruct
 
 
-@deprecated(deprecated_since="3.1.0", removed_from="3.4.0", target=_make_divisible_current_version)
+@deprecated(deprecated_since="3.1.0", removed_from="3.5.0", target=_make_divisible_current_version)
 def make_divisible(x: int, divisor: int, ceil: bool = True) -> int:
     """
     Returns x evenly divisible by divisor.
@@ -144,17 +144,17 @@ def make_divisible(x: int, divisor: int, ceil: bool = True) -> int:
     return _make_divisible_current_version(x=x, divisor=divisor, ceil=ceil)
 
 
-@deprecated(deprecated_since="3.1.0", removed_from="3.4.0", target=BasicResNetBlock, reason="This block was renamed to BasicResNetBlock for better clarity.")
+@deprecated(deprecated_since="3.1.0", removed_from="3.5.0", target=BasicResNetBlock, reason="This block was renamed to BasicResNetBlock for better clarity.")
 class BasicBlock(BasicResNetBlock):
     ...
 
 
-@deprecated(deprecated_since="3.1.0", removed_from="3.4.0", target=NewBottleneck, reason="This block was renamed to BasicResNetBlock for better clarity.")
+@deprecated(deprecated_since="3.1.0", removed_from="3.5.0", target=NewBottleneck, reason="This block was renamed to BasicResNetBlock for better clarity.")
 class Bottleneck(NewBottleneck):
     ...
 
 
-@deprecated(deprecated_since="3.1.0", removed_from="3.4.0", target=CurrVersionHpmStruct)
+@deprecated(deprecated_since="3.1.0", removed_from="3.5.0", target=CurrVersionHpmStruct)
 class HpmStruct(CurrVersionHpmStruct):
     ...
 

tests/integration_tests/yolo_nas_pose_integration_test.py

@@ -5,6 +5,7 @@
 from torch.utils.data import DataLoader
 
 from super_gradients import setup_device
+from super_gradients.common import MultiGPUMode
 from super_gradients.common.abstractions.abstract_logger import get_logger
 from super_gradients.common.environment.cfg_utils import load_dataset_params
 from super_gradients.common.object_names import Models
@@ -65,7 +66,7 @@ def _coco2017_val_yolo_nas_pose(self) -> DataLoader:
 
     def _predict_and_evaluate(self, model, experiment_name):
         device = "cuda" if torch.cuda.is_available() else "cpu"
-        setup_device(device=device)
+        setup_device(device=device, multi_gpu=MultiGPUMode.OFF)
         trainer = Trainer(experiment_name)
         metric = PoseEstimationMetrics(
             post_prediction_callback=model.get_post_prediction_callback(conf=0.01, iou=0.7, post_nms_max_predictions=30),