[proto] Ported all transforms to the new API (#6305)

* [proto] Added few transforms tests, part 1 (#6262)

* Added supported/unsupported data checks in the tests for cutmix/mixup

* Added RandomRotation, RandomAffine transforms tests

* Added tests for RandomZoomOut, Pad

* Update test_prototype_transforms.py

* Added RandomCrop transform and tests (#6271)

* [proto] Added GaussianBlur transform and tests (#6273)

* Added GaussianBlur transform and tests

* Fixing code format

* Copied correctness test

* [proto] Added random color transforms and tests (#6275)

* Added random color transforms and tests

* Disable smoke test for RandomSolarize, RandomAdjustSharpness

* Added RandomPerspective and tests (#6284)

- replaced real image creation by mocks for other tests

* Added more functional tests (#6285)

* [proto] Added elastic transform and tests (#6295)

* WIP [proto] Added functional elastic transform with tests

* Added more functional tests

* WIP on elastic op

* Added elastic transform and tests

* Added tests

* Added tests for ElasticTransform

* Try to format code as in #5106

* Fixed bug in affine get_params test

* Implemented RandomErase on PIL input as fallback to tensors (#6309)

Added tests

* Added image_size computation for BoundingBox.rotate if expand (#6319)

* Added image_size computation for BoundingBox.rotate if expand

* Added tests

* Added erase_image_pil and eager/jit erase_image_tensor test (#6320)

* Updates according to the review

Co-authored-by: Vasilis Vryniotis <[email protected]>

Author: vfdev-5

test/test_functional_tensor.py

@@ -1352,16 +1352,24 @@ def test_ten_crop(device):
         assert_equal(transformed_batch, s_transformed_batch)
 
 
+def test_elastic_transform_asserts():
+    with pytest.raises(TypeError, match="Argument displacement should be a Tensor"):
+        _ = F.elastic_transform("abc", displacement=None)
+
+    with pytest.raises(TypeError, match="img should be PIL Image or Tensor"):
+        _ = F.elastic_transform("abc", displacement=torch.rand(1))
+
+    img_tensor = torch.rand(1, 3, 32, 24)
+    with pytest.raises(ValueError, match="Argument displacement shape should"):
+        _ = F.elastic_transform(img_tensor, displacement=torch.rand(1, 2))
+
+
 @pytest.mark.parametrize("device", cpu_and_gpu())
 @pytest.mark.parametrize("interpolation", [NEAREST, BILINEAR, BICUBIC])
 @pytest.mark.parametrize("dt", [None, torch.float32, torch.float64, torch.float16])
 @pytest.mark.parametrize(
     "fill",
-    [
-        None,
-        [255, 255, 255],
-        (2.0,),
-    ],
+    [None, [255, 255, 255], (2.0,)],
 )
 def test_elastic_transform_consistency(device, interpolation, dt, fill):
     script_elastic_transform = torch.jit.script(F.elastic_transform)