Add call for decoupled image and text ops

Signed-off-by: alex-yuyue <yue.yu1@huawei.com>

mindspore/ccsrc/minddata/dataset/api/execute.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -14,10 +14,11 @@
  * limitations under the License.
  */
 
-#include "minddata/dataset/include/execute.h"
+#include "minddata/dataset/core/tensor_row.h"
 #ifdef ENABLE_ANDROID
 #include "minddata/dataset/include/de_tensor.h"
 #endif
+#include "minddata/dataset/include/execute.h"
 #include "minddata/dataset/include/tensor.h"
 #include "minddata/dataset/kernels/tensor_op.h"
 #ifndef ENABLE_ANDROID
@@ -84,5 +85,25 @@ std::shared_ptr<dataset::Tensor> Execute::operator()(std::shared_ptr<dataset::Te
   return de_output;
 }
 
+Status Execute::operator()(const std::vector<std::shared_ptr<Tensor>> &input_tensor_list,
+                           std::vector<std::shared_ptr<Tensor>> *output_tensor_list) {
+  CHECK_FAIL_RETURN_UNEXPECTED(op_ != nullptr, "Input TensorOperation is not valid");
+  CHECK_FAIL_RETURN_UNEXPECTED(!input_tensor_list.empty(), "Input Tensor is not valid");
+
+  TensorRow input, output;
+  std::copy(input_tensor_list.begin(), input_tensor_list.end(), std::back_inserter(input));
+  CHECK_FAIL_RETURN_UNEXPECTED(!input.empty(), "Input Tensor is not valid");
+
+  std::shared_ptr<TensorOp> transform = op_->Build();
+  Status rc = transform->Compute(input, &output);
+  if (rc.IsError()) {
+    // execution failed
+    RETURN_STATUS_UNEXPECTED("Operation execution failed : " + rc.ToString());
+  }
+
+  std::copy(output.begin(), output.end(), std::back_inserter(*output_tensor_list));
+  return Status::OK();
+}
+
 }  // namespace dataset
 }  // namespace mindspore

mindspore/ccsrc/minddata/dataset/api/python/bindings/dataset/include/execute_binding.cc

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -28,14 +28,26 @@ PYBIND_REGISTER(Execute, 0, ([](const py::module *m) {
                       auto execute = std::make_shared<Execute>(toTensorOperation(operation));
                       return execute;
                     }))
-                    .def("__call__", [](Execute &self, std::shared_ptr<Tensor> in) {
+                    .def("__call__",
+                         [](Execute &self, std::shared_ptr<Tensor> in) {
                            std::shared_ptr<Tensor> out = self(in);
                            if (out == nullptr) {
                              THROW_IF_ERROR([]() {
-                          RETURN_STATUS_UNEXPECTED("Failed to execute op in eager mode, please check ERROR log above.");
+                               RETURN_STATUS_UNEXPECTED(
+                                 "Failed to execute op in eager mode, please check ERROR log above.");
                              }());
                            }
                            return out;
+                         })
+                    .def("__call__", [](Execute &self, const std::vector<std::shared_ptr<Tensor>> &input_tensor_list) {
+                      std::vector<std::shared_ptr<Tensor>> output_tensor_list;
+                      THROW_IF_ERROR(self(input_tensor_list, &output_tensor_list));
+                      if (output_tensor_list.empty()) {
+                        THROW_IF_ERROR([]() {
+                          RETURN_STATUS_UNEXPECTED("Failed to execute op in eager mode, please check ERROR log above.");
+                        }());
+                      }
+                      return output_tensor_list;
                     });
                 }));
 }  // namespace dataset

mindspore/ccsrc/minddata/dataset/include/execute.h

@@ -1,5 +1,5 @@
 /**
- * Copyright 2020 Huawei Technologies Co., Ltd
+ * Copyright 2020-2021 Huawei Technologies Co., Ltd
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
@@ -43,16 +43,23 @@ class Execute {
 
 #ifdef ENABLE_ANDROID
   /// \brief callable function to execute the TensorOperation in eager mode
-  /// \param[inout] input - the tensor to be transformed
+  /// \param[in] input - the tensor to be transformed
   /// \return - the output tensor, nullptr if Compute fails
   std::shared_ptr<tensor::MSTensor> operator()(std::shared_ptr<tensor::MSTensor> input);
 #endif
 
   /// \brief callable function to execute the TensorOperation in eager mode
-  /// \param[inout] input - the tensor to be transformed
+  /// \param[in] input - the tensor to be transformed
   /// \return - the output tensor, nullptr if Compute fails
   std::shared_ptr<dataset::Tensor> operator()(std::shared_ptr<dataset::Tensor> input);
 
+  /// \brief callable function to execute the TensorOperation in eager mode
+  /// \param[in] input_tensor_list - the tensor to be transformed
+  /// \param[out] out - the result tensor after transform
+  /// \return - Status
+  Status operator()(const std::vector<std::shared_ptr<Tensor>> &input_tensor_list,
+                    std::vector<std::shared_ptr<Tensor>> *out);
+
  private:
   std::shared_ptr<TensorOperation> op_;
 };

mindspore/dataset/transforms/c_transforms.py

@@ -1,4 +1,4 @@
-# Copyright 2019 Huawei Technologies Co., Ltd
+# Copyright 2019-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -26,6 +26,14 @@ from .validators import check_num_classes, check_de_type, check_fill_value, chec
 from ..core.datatypes import mstype_to_detype
 
 
+class TensorOperation:
+    def __call__(self):
+        raise NotImplementedError("TensorOperation has to implement __call__() method.")
+
+    def parse(self):
+        raise NotImplementedError("TensorOperation has to implement parse() method.")
+
+
 class OneHot(cde.OneHotOp):
     """
     Tensor operation to apply one hot encoding.
@@ -304,7 +312,7 @@ class Unique(cde.UniqueOp):
     Also return an index tensor that contains the index of each element of the
     input tensor in the Unique output tensor.
 
-    Finally, return a count tensor that constains the count of each element of
+    Finally, return a count tensor that contains the count of each element of
     the output tensor in the input tensor.
 
     Note:

mindspore/dataset/transforms/validators.py

@@ -1,4 +1,4 @@
-# Copyright 2019 Huawei Technologies Co., Ltd
+# Copyright 2019-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -237,8 +237,8 @@ def check_compose_list(method):
         type_check(transforms, (list,), transforms)
         if not transforms:
             raise ValueError("transforms list is empty.")
-        for i, transfrom in enumerate(transforms):
-            if not callable(transfrom):
+        for i, transform in enumerate(transforms):
+            if not callable(transform):
                 raise ValueError("transforms[{}] is not callable.".format(i))
         return method(self, *args, **kwargs)
 
@@ -269,9 +269,10 @@ def check_random_apply(method):
         [transforms, prob], _ = parse_user_args(method, *args, **kwargs)
         type_check(transforms, (list,), "transforms")
 
-        for i, transfrom in enumerate(transforms):
-            if not callable(transfrom):
-                raise ValueError("transforms[{}] is not callable.".format(i))
+        for i, transform in enumerate(transforms):
+            if str(transform).find("c_transform") >= 0:
+                raise ValueError("transforms[{}] is not a py transforms. Should not use a c transform in py transform" \
+                    .format(i))
 
         if prob is not None:
             type_check(prob, (float, int,), "prob")
@@ -290,9 +291,10 @@ def check_transforms_list(method):
         [transforms], _ = parse_user_args(method, *args, **kwargs)
 
         type_check(transforms, (list,), "transforms")
-        for i, transfrom in enumerate(transforms):
-            if not callable(transfrom):
-                raise ValueError("transforms[{}] is not callable.".format(i))
+        for i, transform in enumerate(transforms):
+            if str(transform).find("c_transform") >= 0:
+                raise ValueError("transforms[{}] is not a py transforms. Should not use a c transform in py transform" \
+                    .format(i))
         return method(self, *args, **kwargs)
 
     return new_method

tests/ut/python/dataset/test_HWC2CHW.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -29,6 +29,20 @@ DATA_DIR = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
 SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
 
 
+def test_HWC2CHW_callable():
+    """
+    Test HWC2CHW is callable
+    """
+    logger.info("Test HWC2CHW callable")
+    img = np.fromfile("../data/dataset/apple.jpg", dtype=np.uint8)
+    logger.info("Image.type: {}, Image.shape: {}".format(type(img), img.shape))
+
+    img = c_vision.Decode()(img)
+    img = c_vision.HWC2CHW()(img)
+    logger.info("Image.type: {}, Image.shape: {}".format(type(img), img.shape))
+    assert img.shape == (3, 2268, 4032)
+
+
 def test_HWC2CHW(plot=False):
     """
     Test HWC2CHW
@@ -122,6 +136,7 @@ def test_HWC2CHW_comp(plot=False):
 
 
 if __name__ == '__main__':
+    test_HWC2CHW_callable()
     test_HWC2CHW(True)
     test_HWC2CHW_md5()
     test_HWC2CHW_comp(True)

tests/ut/python/dataset/test_compose.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -219,7 +219,7 @@ def test_c_py_compose_vision_module(plot=False, run_golden=True):
 
 def test_py_transforms_with_c_vision():
     """
-    These examples will fail, as py_transforms.Random(Apply/Choice/Order) expect callable functions
+    These examples will fail, as c_transform should not be used in py_transforms.Random(Apply/Choice/Order)
     """
 
     ds.config.set_seed(0)
@@ -236,15 +236,15 @@ def test_py_transforms_with_c_vision():
 
     with pytest.raises(ValueError) as error_info:
         test_config(py_transforms.RandomApply([c_vision.RandomResizedCrop(200)]))
-    assert "transforms[0] is not callable." in str(error_info.value)
+    assert "transforms[0] is not a py transforms." in str(error_info.value)
 
     with pytest.raises(ValueError) as error_info:
         test_config(py_transforms.RandomChoice([c_vision.RandomResizedCrop(200)]))
-    assert "transforms[0] is not callable." in str(error_info.value)
+    assert "transforms[0] is not a py transforms." in str(error_info.value)
 
     with pytest.raises(ValueError) as error_info:
         test_config(py_transforms.RandomOrder([np.array, c_vision.RandomResizedCrop(200)]))
-    assert "transforms[1] is not callable." in str(error_info.value)
+    assert "transforms[1] is not a py transforms." in str(error_info.value)
 
     with pytest.raises(RuntimeError) as error_info:
         test_config([py_transforms.OneHotOp(20, 0.1)])

tests/ut/python/dataset/test_invert.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -29,6 +29,21 @@ DATA_DIR = "../data/dataset/testImageNetData/train/"
 GENERATE_GOLDEN = False
 
 
+def test_invert_callable():
+    """
+    Test Invert is callable
+    """
+    logger.info("Test Invert callable")
+    img = np.fromfile("../data/dataset/apple.jpg", dtype=np.uint8)
+    logger.info("Image.type: {}, Image.shape: {}".format(type(img), img.shape))
+
+    img = C.Decode()(img)
+    img = C.Invert()(img)
+    logger.info("Image.type: {}, Image.shape: {}".format(type(img), img.shape))
+
+    assert img.shape == (2268, 4032, 3)
+
+
 def test_invert_py(plot=False):
     """
     Test Invert python op
@@ -247,6 +262,7 @@ def test_invert_md5_c():
 
 
 if __name__ == "__main__":
+    test_invert_callable()
     test_invert_py(plot=False)
     test_invert_c(plot=False)
     test_invert_py_c(plot=False)

tests/ut/python/dataset/test_random_crop_and_resize.py

@@ -1,4 +1,4 @@
-# Copyright 2019 Huawei Technologies Co., Ltd
+# Copyright 2019-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -34,6 +34,22 @@ SCHEMA_DIR = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
 GENERATE_GOLDEN = False
 
 
+def test_random_crop_and_resize_callable():
+    """
+    Test RandomCropAndResize op is callable
+    """
+    logger.info("test_random_crop_and_resize_callable")
+    img = np.fromfile("../data/dataset/apple.jpg", dtype=np.uint8)
+    logger.info("Image.type: {}, Image.shape: {}".format(type(img), img.shape))
+
+    decode_op = c_vision.Decode()
+    img = decode_op(img)
+
+    random_crop_and_resize_op = c_vision.RandomResizedCrop((256, 512), (2, 2), (1, 3))
+    img = random_crop_and_resize_op(img)
+    assert np.shape(img) == (256, 512, 3)
+
+
 def test_random_crop_and_resize_op_c(plot=False):
     """
     Test RandomCropAndResize op in c transforms
@@ -389,6 +405,7 @@ def test_random_crop_and_resize_06():
 
 
 if __name__ == "__main__":
+    test_random_crop_and_resize_callable()
     test_random_crop_and_resize_op_c(True)
     test_random_crop_and_resize_op_py(True)
     test_random_crop_and_resize_op_py_ANTIALIAS()

tests/ut/python/dataset/test_text_jieba_tokenizer.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -16,6 +16,7 @@ import numpy as np
 import mindspore.dataset as ds
 from mindspore.dataset.text import JiebaTokenizer
 from mindspore.dataset.text import JiebaMode, to_str
+from mindspore import log as logger
 
 DATA_FILE = "../data/dataset/testJiebaDataset/3.txt"
 DATA_ALL_FILE = "../data/dataset/testJiebaDataset/*"
@@ -24,6 +25,23 @@ HMM_FILE = "../data/dataset/jiebadict/hmm_model.utf8"
 MP_FILE = "../data/dataset/jiebadict/jieba.dict.utf8"
 
 
+def test_jieba_callable():
+    """
+    Test jieba tokenizer op is callable
+    """
+    logger.info("test_jieba_callable")
+    jieba_op1 = JiebaTokenizer(HMM_FILE, MP_FILE, mode=JiebaMode.MP)
+    jieba_op2 = JiebaTokenizer(HMM_FILE, MP_FILE, mode=JiebaMode.HMM)
+
+    text1 = "今天天气太好了我们一起去外面玩吧"
+    text2 = "男默女泪市长江大桥"
+    assert np.array_equal(jieba_op1(text1), ['今天天气', '太好了', '我们', '一起', '去', '外面', '玩吧'])
+    assert np.array_equal(jieba_op2(text1), ['今天', '天气', '太', '好', '了', '我们', '一起', '去', '外面', '玩', '吧'])
+
+    jieba_op1.add_word("男默女泪")
+    assert np.array_equal(jieba_op1(text2), ['男默女泪', '市', '长江大桥'])
+
+
 def test_jieba_1():
     """Test jieba tokenizer with MP mode"""
     data = ds.TextFileDataset(DATA_FILE)
@@ -457,6 +475,7 @@ def test_jieba_6():
 
 
 if __name__ == "__main__":
+    test_jieba_callable()
     test_jieba_1()
     test_jieba_1_1()
     test_jieba_1_2()

tests/ut/python/dataset/test_uniform_augment.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -28,6 +28,24 @@ from util import visualize_list, diff_mse
 DATA_DIR = "../data/dataset/testImageNetData/train/"
 
 
+def test_uniform_augment_callable(num_ops=2):
+    """
+    Test UniformAugment is callable
+    """
+    logger.info("test_uniform_augment_callable")
+    img = np.fromfile("../data/dataset/apple.jpg", dtype=np.uint8)
+    logger.info("Image.type: {}, Image.shape: {}".format(type(img), img.shape))
+
+    decode_op = C.Decode()
+    img = decode_op(img)
+
+    transforms_ua = [C.RandomCrop(size=[400, 400], padding=[32, 32, 32, 32]),
+                     C.RandomCrop(size=[400, 400], padding=[32, 32, 32, 32])]
+    uni_aug = C.UniformAugment(transforms=transforms_ua, num_ops=num_ops)
+    img = uni_aug([img, img])
+    assert ((np.shape(img) == (2, 2268, 4032, 3)) or (np.shape(img) == (1, 400, 400, 3)))
+
+
 def test_uniform_augment(plot=False, num_ops=2):
     """
     Test UniformAugment
@@ -262,6 +280,7 @@ def test_cpp_uniform_augment_random_crop_badinput(num_ops=1):
 
 
 if __name__ == "__main__":
+    test_uniform_augment_callable(num_ops=2)
     test_uniform_augment(num_ops=1, plot=True)
     test_cpp_uniform_augment(num_ops=1, plot=True)
     test_cpp_uniform_augment_exception_pyops(num_ops=1)

tests/ut/python/dataset/test_vocab.py

@@ -1,4 +1,4 @@
-# Copyright 2020 Huawei Technologies Co., Ltd
+# Copyright 2020-2021 Huawei Technologies Co., Ltd
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -18,6 +18,7 @@ import numpy as np
 import mindspore.dataset as ds
 import mindspore.dataset.text as text
 import mindspore.common.dtype as mstype
+from mindspore import log as logger
 
 # this file contains "home is behind the world head" each word is 1 line
 DATA_FILE = "../data/dataset/testVocab/words.txt"
@@ -25,6 +26,16 @@ VOCAB_FILE = "../data/dataset/testVocab/vocab_list.txt"
 SIMPLE_VOCAB_FILE = "../data/dataset/testVocab/simple_vocab_list.txt"
 
 
+def test_lookup_callable():
+    """
+    Test lookup is callable
+    """
+    logger.info("test_lookup_callable")
+    vocab = text.Vocab.from_list(['深', '圳', '欢', '迎', '您'])
+    lookup = text.Lookup(vocab)
+    word = "迎"
+    assert lookup(word) == 3
+
 def test_from_list_tutorial():
     vocab = text.Vocab.from_list("home IS behind the world ahead !".split(" "), ["<pad>", "<unk>"], True)
     lookup = text.Lookup(vocab, "<unk>")
@@ -171,6 +182,7 @@ def test_lookup_cast_type():
 
 
 if __name__ == '__main__':
+    test_lookup_callable()
     test_from_dict_exception()
     test_from_list_tutorial()
     test_from_file_tutorial()