add skip dataset op

mindspore/ccsrc/dataset/api/de_pipeline.cc

@@ -47,6 +47,7 @@ static std::unordered_map<uint32_t, pFunction> g_parse_op_func_ = {{kStorage, &D
                                                                    {kMap, &DEPipeline::ParseMapOp},
                                                                    {kBatch, &DEPipeline::ParseBatchOp},
                                                                    {kRepeat, &DEPipeline::ParseRepeatOp},
+                                                                   {kSkip, &DEPipeline::ParseSkipOp},
                                                                    {kZip, &DEPipeline::ParseZipOp},
                                                                    {kRename, &DEPipeline::ParseRenameOp},
                                                                    {kDeviceQueue, &DEPipeline::ParseDeviceQueueOp},
@@ -511,6 +512,17 @@ Status DEPipeline::ParseRepeatOp(const py::dict &args, std::shared_ptr<DatasetOp
   return Status::OK();
 }
 
+Status DEPipeline::ParseSkipOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr) {
+  if (args["count"].is_none()) {
+    std::string err_msg = "Error: count is invalid or not set.";
+    RETURN_STATUS_UNEXPECTED(err_msg);
+  }
+  std::shared_ptr<SkipOp> op;
+  RETURN_IF_NOT_OK(SkipOp::Builder(ToInt(args["count"])).Build(&op));
+  *ptr = op;
+  return Status::OK();
+}
+
 Status DEPipeline::ParseGeneratorOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr) {
   std::shared_ptr<GeneratorOp::Builder> builder = std::make_shared<GeneratorOp::Builder>();
   for (auto arg : args) {

mindspore/ccsrc/dataset/api/de_pipeline.h

@@ -42,6 +42,7 @@ enum OpName {
   kBatch,
   kCache,
   kRepeat,
+  kSkip,
   kTake,
   kZip,
   kMap,
@@ -107,6 +108,8 @@ class DEPipeline {
 
   Status ParseRepeatOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
 
+  Status ParseSkipOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
+
   Status ParseBatchOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);
 
   Status ParseGeneratorOp(const py::dict &args, std::shared_ptr<DatasetOp> *ptr);

mindspore/ccsrc/dataset/api/python_bindings.cc

@@ -446,6 +446,7 @@ PYBIND11_MODULE(_c_dataengine, m) {
     .value("MINDRECORD", OpName::kMindrecord)
     .value("CACHE", OpName::kCache)
     .value("REPEAT", OpName::kRepeat)
+    .value("SKIP", OpName::kSkip)
     .value("TAKE", OpName::kTake)
     .value("ZIP", OpName::kZip)
     .value("MAP", OpName::kMap)

mindspore/ccsrc/dataset/core/client.h

@@ -32,6 +32,7 @@
 #include "dataset/engine/datasetops/project_op.h"
 #include "dataset/engine/datasetops/rename_op.h"
 #include "dataset/engine/datasetops/repeat_op.h"
+#include "dataset/engine/datasetops/skip_op.h"
 #include "dataset/engine/datasetops/shuffle_op.h"
 #include "dataset/engine/datasetops/source/generator_op.h"
 #include "dataset/engine/datasetops/source/mindrecord_op.h"

mindspore/ccsrc/dataset/engine/datasetops/CMakeLists.txt

@@ -11,6 +11,7 @@ add_library(engine-datasetops OBJECT
     project_op.cc
     rename_op.cc
     repeat_op.cc
+    skip_op.cc
     shuffle_op.cc
     zip_op.cc
     )

mindspore/ccsrc/dataset/engine/datasetops/skip_op.cc

@@ -0,0 +1,128 @@
+/**
+ * Copyright 2020 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.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include <iostream>
+#include <utility>
+
+#include "dataset/engine/data_buffer.h"
+#include "dataset/engine/datasetops/skip_op.h"
+#include "dataset/engine/db_connector.h"
+#include "dataset/engine/execution_tree.h"
+
+#include "utils/log_adapter.h"
+
+namespace mindspore {
+namespace dataset {
+// Builder constructor.  Creates the builder object.
+SkipOp::Builder::Builder(int32_t count) : build_max_skips_(count) {}
+
+Status SkipOp::Builder::SanityCheck() const {
+  if (build_max_skips_ < 0) {
+    std::string err_msg("Skip count must be positive integer or 0.");
+    RETURN_STATUS_UNEXPECTED(err_msg);
+  }
+  return Status::OK();
+}
+
+// The builder "build" method creates the final object.
+Status SkipOp::Builder::Build(std::shared_ptr<SkipOp> *ptr) {
+  RETURN_IF_NOT_OK(SanityCheck());
+  *ptr = std::make_shared<SkipOp>(build_max_skips_);
+  return Status::OK();
+}
+
+// Constructor of the SkipOp.
+SkipOp::SkipOp(int32_t count) : PipelineOp(0), max_skips_(count), skip_count_(0) {}
+
+// Destructor
+SkipOp::~SkipOp() {}
+
+// A print method typically used for debugging
+void SkipOp::Print(std::ostream &out, bool show_all) const {
+  // Call base class printer first
+  PipelineOp::Print(out, show_all);
+
+  // Then display our own stuff
+  out << "SkipOp:"
+      << "\nCurrent skip count: " << skip_count_ << "\nMax skip count: " << max_skips_;
+}
+
+// Since the buffer may contain multi rows, this function will drop the rows
+// that need to skip in it, and then return the buffer.
+Status SkipOp::GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id, bool retry_if_eoe) {
+  if (child_.empty()) {
+    RETURN_STATUS_UNEXPECTED("SkipOp can't be the leaf node.");
+  }
+
+  std::unique_ptr<DataBuffer> buf;
+  // Drop first max_skips_ rows
+  while (skip_count_ < max_skips_) {
+    RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&buf, worker_id, true));
+    if (buf->eoe() || buf->eof()) {
+      break;
+    }
+
+    // Consider the rows of buffer more than 1
+    TensorRow drop_row;
+    int row_num = buf->NumRows();
+    for (int i = 0; i < row_num; i++) {
+      RETURN_IF_NOT_OK(buf->PopRow(&drop_row));
+      if (++skip_count_ == max_skips_) {
+        break;
+      }
+    }
+  }
+
+  // If buffer is none or the rows of buffer is 0,
+  // then get a buffer from child.
+  if (!buf || buf->NumRows() == 0) {
+    RETURN_IF_NOT_OK(child_[0]->GetNextBuffer(&buf, worker_id, true));
+  }
+
+  // Handling eoe and eof
+  if (buf->eoe() || buf->eof()) {
+    RETURN_IF_NOT_OK(EoeReceived(worker_id));
+    if (state_ == OpState::kDeOpIdle) {
+      *p_buffer = std::move(buf);
+      return Status::OK();
+    }
+  }
+
+  *p_buffer = std::move(buf);
+  return Status::OK();
+}
+
+// Base-class override for handling cases when an eoe is received.
+Status SkipOp::EoeReceived(int32_t worker_id) {
+  skip_count_ = 0;
+  state_ = OpState::kDeOpIdle;
+  return Status::OK();
+}
+
+// Class functor operator () override.
+// Most dataset ops operate by launching a thread (see ExecutionTree).
+// However, the SkipOp is defined as a inlined operator, so it is invalid to
+// launch the functor since this op runs inlined inside another operator.  The
+// function is overloaded to ensure that it is not called by mistake (it will
+// generate an error).
+Status SkipOp::operator()() { RETURN_STATUS_UNEXPECTED("Logic error. SkipOp is an inlined operator."); }
+
+// Base-class override for handling cases when an eof is received.
+Status SkipOp::EofReceived(int32_t worker_id) {
+  MS_LOG(INFO) << "Skip operator EOF received, do nothing now.";
+  return Status::OK();
+}
+}  // namespace dataset
+}  // namespace mindspore

mindspore/ccsrc/dataset/engine/datasetops/skip_op.h

@@ -0,0 +1,95 @@
+/**
+ * Copyright 2020 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.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#ifndef DATASET_ENGINE_DATASETOPS_SKIP_OP_H_
+#define DATASET_ENGINE_DATASETOPS_SKIP_OP_H_
+
+#include <memory>
+#include <string>
+#include <vector>
+#include "dataset/engine/datasetops/pipeline_op.h"
+
+namespace mindspore {
+namespace dataset {
+class SkipOp : public PipelineOp {
+ public:
+  class Builder {
+   public:
+    // Builder constructor.  Creates the builder object.
+    // @note No default args
+    // @param count - The number of skip to do
+    // @return This is a constructor.
+    explicit Builder(int32_t count);
+
+    // Default destructor
+    ~Builder() = default;
+
+    // The builder "build" method creates the final object.
+    // @return shared_ptr to the new StorageOp object
+    Status Build(std::shared_ptr<SkipOp> *);
+
+   private:
+    int32_t build_max_skips_;
+
+    Status SanityCheck() const;
+  };
+
+  // Constructor of the SkipOp.
+  // @note The builder class should be used to call it
+  // @param count - The number of skips to do
+  explicit SkipOp(int32_t count);
+
+  // Destructor
+  ~SkipOp();
+
+  // A print method typically used for debugging
+  // @param out - The output stream to write output to
+  // @param show_all - A bool to control if you want to show all info or just a summary
+  void Print(std::ostream &out, bool show_all) const override;
+
+  // Class functor operator () override.
+  // Most dataset ops operate by launching a thread (see ExecutionTree).
+  // However, the SkipOp is defined as a inlined operator, so it is invalid to launch the
+  // functor since this op runs inlined inside another operator.  The function is overloaded to
+  // ensure that it is not called by mistake (it will generate an error).
+  // @return Status - The error code return
+  Status operator()() override;
+
+  // This function returns the buffer that is at the top of our output connector. The caller is
+  // typically our parent node, when the parent is asking us to provide the next buffer of data.
+  // Since SkipOp is an inlined op, getting a buffer from us will simply bounce you to get
+  // a buffer from our child.
+  // @param p_buffer - output pointer to the buffer that it will fetch.
+  // @param worker_id - The worker id
+  // @param retry_if_eoe Set this flag to true to allow calling pop() again after the first pop() returns EOE.
+  // @return Status - The error code return
+  Status GetNextBuffer(std::unique_ptr<DataBuffer> *p_buffer, int32_t worker_id, bool retry_if_eoe) override;
+
+  // Base-class override for handling cases when an eoe is received.
+  // @param worker_id - The worker id
+  Status EoeReceived(int32_t worker_id) override;
+
+  // Base-class override for handling cases when an eof is received.
+  // @param worker_id - The worker id
+  Status EofReceived(int32_t worker_id) override;
+
+ private:
+  int32_t max_skips_;   // The number of skips that the user requested
+  int32_t skip_count_;  // A counter for the current number of executed skips
+};
+}  // namespace dataset
+}  // namespace mindspore
+
+#endif  // DATASET_ENGINE_DATASETOPS_SKIP_OP_H_

mindspore/dataset/engine/datasets.py

@@ -35,7 +35,7 @@ from mindspore._c_expression import typing
 from mindspore import log as logger
 from . import samplers
 from .iterators import DictIterator, TupleIterator
-from .validators import check, check_batch, check_shuffle, check_map, check_repeat, check_zip, check_rename, \
+from .validators import check, check_batch, check_shuffle, check_map, check_repeat, check_skip, check_zip, check_rename, \
     check_project, check_imagefolderdatasetv2, check_mnist_cifar_dataset, check_manifestdataset, \
     check_tfrecorddataset, check_vocdataset, check_celebadataset, check_minddataset, check_generatordataset, \
     check_zip_dataset, check_add_column
@@ -423,6 +423,25 @@ class Dataset:
             return self
         return RepeatDataset(self, count)
 
+    @check_skip
+    def skip(self, count):
+        """
+        Skip the first N elements of this dataset.
+
+        Args:
+            count (int): Number of elements the dataset should be skipped.
+
+        Returns:
+            SkipDataset, dataset skipped.
+
+        Examples:
+            >>> import mindspore.dataset as ds
+            >>> # data is an instance of Dataset object.
+            >>> # creates a dataset which skips first 3 elements from data
+            >>> data = data.skip(3)
+        """
+        return SkipDataset(self, count)
+
     @check_zip_dataset
     def zip(self, datasets):
         """
@@ -1081,6 +1100,39 @@ class RepeatDataset(DatasetOp):
         """
         return self.count
 
+class SkipDataset(DatasetOp):
+    """
+    The result of applying Skip operator to the input Dataset.
+
+    Args:
+        datasets (tuple): A tuple of datasets to be skipped.
+        count (int): Number of rows the dataset should be skipped.
+    """
+
+    def __init__(self, input_dataset, count):
+        super().__init__()
+        self.count = count
+        self.input.append(input_dataset)
+        input_dataset.output.append(self)
+        self._input_indexs = input_dataset.input_indexs
+
+    def get_args(self):
+        args = super().get_args()
+        args["count"] = self.count
+        return args
+
+    def get_dataset_size(self):
+        """
+        Get the number of batches in an epoch.
+
+        Return:
+            Number, number of batches.
+        """
+        child_size = self.input[0].get_dataset_size()
+        output_size = 0
+        if self.count >= 0 and self.count < child_size:
+            output_size = child_size - self.count
+        return output_size
 
 class ZipDataset(DatasetOp):
     """

mindspore/dataset/engine/iterators.py

@@ -127,6 +127,8 @@ class Iterator:
             op_type = OpName.MAP
         elif isinstance(dataset, de.RepeatDataset):
             op_type = OpName.REPEAT
+        elif isinstance(dataset, de.SkipDataset):
+            op_type = OpName.SKIP
         elif isinstance(dataset, de.StorageDataset):
             op_type = OpName.STORAGE
         elif isinstance(dataset, de.ImageFolderDatasetV2):

mindspore/dataset/engine/serializer_deserializer.py

@@ -297,6 +297,9 @@ def create_node(node):
     elif dataset_op == 'RepeatDataset':
         pyobj = de.Dataset().repeat(node.get('count'))
 
+    elif dataset_op == 'SkipDataset':
+        pyobj = de.Dataset().skip(node.get('count'))
+
     elif dataset_op == 'MapDataset':
         tensor_ops = construct_tensor_ops(node.get('operations'))
         pyobj = de.Dataset().map(node.get('input_columns'), tensor_ops, node.get('output_columns'),

mindspore/dataset/engine/validators.py

@@ -709,6 +709,20 @@ def check_repeat(method):
 
     return new_method
 
+def check_skip(method):
+    """check the input arguments of skip."""
+    @wraps(method)
+    def new_method(*args, **kwargs):
+        param_dict = make_param_dict(method, args, kwargs)
+
+        count = param_dict.get('count')
+        check_type(count, 'count', int)
+        if count < 0:
+            raise ValueError("Skip count must be positive integer or 0.")
+
+        return method(*args, **kwargs)
+
+    return new_method
 
 def check_zip(method):
     """check the input arguments of zip."""

tests/ut/cpp/dataset/CMakeLists.txt

@@ -41,6 +41,7 @@ SET(DE_UT_SRCS
     random_vertical_flip_op_test.cc
     rename_op_test.cc
     repeat_op_test.cc
+    skip_op_test.cc
     rescale_op_test.cc
     resize_bilinear_op_test.cc
     resize_op_test.cc

tests/ut/cpp/dataset/skip_op_test.cc

@@ -0,0 +1,91 @@
+/**
+ * Copyright 2020 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.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+#include "dataset/util/circular_pool.h"
+#include "dataset/core/client.h"
+#include "common/common.h"
+#include "gtest/gtest.h"
+#include "utils/log_adapter.h"
+
+using namespace mindspore::dataset;
+using mindspore::MsLogLevel::INFO;
+using mindspore::ExceptionType::NoExceptionType;
+using mindspore::LogStream;
+
+class MindDataTestSkipOp : public UT::DatasetOpTesting {};
+
+TEST_F(MindDataTestSkipOp, TestSkipOpFuntions) {
+  // Start with an empty execution tree
+  auto my_tree = std::make_shared<ExecutionTree>();
+
+  std::string dataset_path;
+  dataset_path = datasets_root_path_ + "/testTFTestAllTypes/test.data";
+
+  std::shared_ptr<TFReaderOp> my_tfreader_op;
+  TFReaderOp::Builder builder;
+  builder.SetDatasetFilesList({dataset_path})
+    .SetRowsPerBuffer(16)
+    .SetWorkerConnectorSize(16)
+    .SetNumWorkers(16);
+  std::unique_ptr<DataSchema> schema = std::make_unique<DataSchema>();
+  schema->LoadSchemaFile(datasets_root_path_ + "/testTFTestAllTypes/datasetSchema.json", {});
+  builder.SetDataSchema(std::move(schema));
+  Status rc = builder.Build(&my_tfreader_op);  ASSERT_TRUE(rc.IsOk());
+  rc = my_tree->AssociateNode(my_tfreader_op);
+  ASSERT_TRUE(rc.IsOk());
+
+  // SkipOp
+  std::shared_ptr<SkipOp> skip_op = std::make_shared<SkipOp>(5);
+  rc = my_tree->AssociateNode(skip_op);
+  ASSERT_TRUE(rc.IsOk());
+
+  // Set children/root layout.
+  rc = skip_op->AddChild(my_tfreader_op);
+  ASSERT_TRUE(rc.IsOk());
+  rc = my_tree->AssignRoot(skip_op);
+  ASSERT_TRUE(rc.IsOk());
+
+  MS_LOG(INFO) << "Launching tree and begin iteration.";
+  rc = my_tree->Prepare();
+
+  ASSERT_TRUE(rc.IsOk());
+
+  rc = my_tree->Launch();
+  ASSERT_TRUE(rc.IsOk());
+
+  // Start the loop of reading tensors from our pipeline
+  DatasetIterator di(my_tree);
+  TensorRow tensor_list;
+  rc = di.FetchNextTensorRow(&tensor_list);
+  ASSERT_TRUE(rc.IsOk());
+
+  int row_count = 0;
+  while (!tensor_list.empty()) {
+    MS_LOG(INFO) << "Row display for row #: " << row_count << ".";
+
+    // Display the tensor by calling the printer on it
+    for (int i = 0; i < tensor_list.size(); i++) {
+      std::ostringstream ss;
+      ss << "(" << tensor_list[i] << "): " << *tensor_list[i] << std::endl;
+      MS_LOG(INFO) << "Tensor print: " << ss.str() << ".";
+    }
+
+    rc = di.FetchNextTensorRow(&tensor_list);
+    ASSERT_TRUE(rc.IsOk());
+    row_count++;
+  }
+
+  ASSERT_EQ(row_count, 7);
+}

tests/ut/python/dataset/test_skip.py

@@ -0,0 +1,130 @@
+# Copyright 2020 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.
+# You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+# ==============================================================================
+
+import numpy as np
+
+import mindspore.dataset.transforms.vision.c_transforms as vision
+import mindspore.dataset as ds
+from mindspore import log as logger
+
+DATA_DIR_TF2 = ["../data/dataset/test_tf_file_3_images/train-0000-of-0001.data"]
+SCHEMA_DIR_TF2 = "../data/dataset/test_tf_file_3_images/datasetSchema.json"
+
+def test_tf_skip():
+    data1 = ds.TFRecordDataset(DATA_DIR_TF2, SCHEMA_DIR_TF2, shuffle=False)
+
+    resize_height, resize_width = 32, 32
+    decode_op = vision.Decode()
+    resize_op = vision.Resize((resize_height, resize_width), interpolation=ds.transforms.vision.Inter.LINEAR)
+    data1 = data1.map(input_columns=["image"], operations=decode_op)
+    data1 = data1.map(input_columns=["image"], operations=resize_op)
+    data1 = data1.skip(2)
+
+    num_iter = 0
+    for item in data1.create_dict_iterator():
+        num_iter += 1
+    assert num_iter == 1
+
+def generator_md():
+    # Create a dataset with [0, 1, 2, 3, 4]
+    for i in range(5):
+        yield (np.array([i]), )
+
+def test_generator_skip():
+    ds1 = ds.GeneratorDataset(generator_md, ["data"])
+
+    # Here ds1 should be [3, 4]
+    ds1 = ds1.skip(3)
+
+    buf = []
+    for data in ds1:
+        buf.append(data[0][0])
+    assert len(buf) == 2
+
+def test_skip_1():
+    ds1 = ds.GeneratorDataset(generator_md, ["data"])
+
+    # Here ds1 should be []
+    ds1 = ds1.skip(7)
+
+    buf = []
+    for data in ds1:
+        buf.append(data[0][0])
+    assert len(buf) == 0
+
+def test_skip_2():
+    ds1 = ds.GeneratorDataset(generator_md, ["data"])
+
+    # Here ds1 should be [0, 1, 2, 3, 4]
+    ds1 = ds1.skip(0)
+
+    buf = []
+    for data in ds1:
+        buf.append(data[0][0])
+    assert len(buf) == 5
+
+def test_skip_repeat_1():
+    ds1 = ds.GeneratorDataset(generator_md, ["data"])
+
+    # Here ds1 should be [0, 1, 2, 3, 4, 0, 1, 2, 3, 4]
+    ds1 = ds1.repeat(2)
+
+    # Here ds1 should be [3, 4, 0, 1, 2, 3, 4]
+    ds1 = ds1.skip(3)
+
+    buf = []
+    for data in ds1:
+        buf.append(data[0][0])
+    assert len(buf) == 7
+
+def test_skip_repeat_2():
+    ds1 = ds.GeneratorDataset(generator_md, ["data"])
+
+    # Here ds1 should be [3, 4]
+    ds1 = ds1.skip(3)
+
+    # Here ds1 should be [3, 4, 3, 4]
+    ds1 = ds1.repeat(2)
+
+    buf = []
+    for data in ds1:
+        buf.append(data[0][0])
+    assert len(buf) == 4
+
+def test_skip_repeat_3():
+    ds1 = ds.GeneratorDataset(generator_md, ["data"])
+
+    # Here ds1 should be [0, 1, 2, 3, 4, 0, 1, 2, 3, 4]
+    ds1 = ds1.repeat(2)
+
+    # Here ds1 should be [3, 4]
+    ds1 = ds1.skip(8)
+
+    # Here ds1 should be [3, 4, 3, 4, 3, 4]
+    ds1 = ds1.repeat(3)
+
+    buf = []
+    for data in ds1:
+        buf.append(data[0][0])
+    assert len(buf) == 6
+
+if __name__ == "__main__":
+    test_tf_skip()
+    test_generator_skip()
+    test_skip_1()
+    test_skip_2()
+    test_skip_repeat_1()
+    test_skip_repeat_2()
+    test_skip_repeat_3()