fix pad op validate issue

mindspore/ccsrc/minddata/dataset/kernels/image/image_utils.cc

@@ -875,8 +875,6 @@ Status Pad(const std::shared_ptr<Tensor> &input, std::shared_ptr<Tensor> *output
     std::shared_ptr<CVTensor> output_cv;
     RETURN_IF_NOT_OK(CVTensor::CreateFromMat(out_image, &output_cv));
     // pad the dimension if shape information is only 2 dimensional, this is grayscale
-    CHECK_FAIL_RETURN_UNEXPECTED(input_cv->Rank() == 3,
-                                 "Pad error: invalid image shape, only support 3 channels image.");
     int num_channels = input_cv->shape()[2];
     if (input_cv->Rank() == 3 && num_channels == 1 && output_cv->Rank() == 2) output_cv->ExpandDim(2);
     *output = std::static_pointer_cast<Tensor>(output_cv);

tests/ut/python/dataset/test_pad.py

@@ -148,20 +148,8 @@ def test_pad_md5():
     filename2 = "pad_01_py_result.npz"
     save_and_check_md5(data2, filename2, generate_golden=GENERATE_GOLDEN)
 
-def test_pad_exception():
-    try:
-        data1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, columns_list=["image"], shuffle=False)
-        pad_op = c_vision.Pad(150)
-        data1 = data1.map(input_columns=["image"], operations=pad_op)
-        for _ in data1.create_dict_iterator():
-            pass
-        assert False
-    except RuntimeError as e:
-        assert "Pad error: invalid image shape, only support 3 channels image" in str(e)
-
 
 if __name__ == "__main__":
     test_pad_op()
     test_pad_grayscale()
     test_pad_md5()
-    test_pad_exception()