Fix cache_admin server start stderr output

Fix TFRecord get_dataset_size() when cached

mindspore/ccsrc/minddata/dataset/engine/cache/cache_admin_arg.cc

@@ -589,16 +589,14 @@ Status CacheAdminArgHandler::StartServer() {
     (void)dup2(fd[0], STDIN_FILENO);
     close(fd[0]);
     std::string msg;
+    std::string buf;
     const uint32_t buf_sz = 1024;
-    msg.resize(buf_sz);
-    auto n = read(0, msg.data(), buf_sz);
+    buf.resize(buf_sz);
+    auto n = read(0, buf.data(), buf_sz);
     // keep reading until we drain the pipe
     while (n > 0) {
-      msg.resize(n);
-      // Not an error, some info message goes to stdout
-      std::cout << msg;
-      msg.resize(buf_sz);
-      n = read(0, msg.data(), buf_sz);
+      msg += buf.substr(0, n);
+      n = read(0, buf.data(), buf_sz);
     }
     if (n < 0) {
       std::string err_msg = "Failed to read from pipeline " + std::to_string(errno);
@@ -613,6 +611,9 @@ Status CacheAdminArgHandler::StartServer() {
       auto exit_status = WEXITSTATUS(status);
       if (exit_status) {
         return Status(StatusCode::kMDUnexpectedError, msg);
+      } else {
+        // Not an error, some info message goes to stdout
+        std::cout << msg;
       }
     }
     return Status::OK();

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/map_node.cc

@@ -176,5 +176,28 @@ Status MapNode::to_json(nlohmann::json *out_json) {
   *out_json = args;
   return Status::OK();
 }
+
+// Gets the dataset size
+Status MapNode::GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_getter, bool estimate,
+                               int64_t *dataset_size) {
+  if (dataset_size_ > 0) {
+    *dataset_size = dataset_size_;
+    return Status::OK();
+  }
+  // If cache is injected after a MapNode, it is possible that the pipeline needs to handle different numbers of rows
+  // compared to a non-cached pipeline. This is mostly true for TFRecord dataset, since it uses row-based sharding
+  // with cache but file-based sharding without cache. However, MapNode couldn't tell whether the leaf below is
+  // TFRecord or not, therefore it doesn't rely on its child here but simply run through the tree.
+  if (!IsSizeDefined() || IsCached()) {
+    RETURN_IF_NOT_OK(size_getter->DryRun(shared_from_this(), dataset_size));
+    dataset_size_ = *dataset_size;
+    return Status::OK();
+  }
+  if (children_.size() == 1) {
+    return children_.front()->GetDatasetSize(size_getter, estimate, dataset_size);
+  } else {
+    RETURN_STATUS_UNEXPECTED("Trying to get dataset size from leaf node, missing override");
+  }
+}
 }  // namespace dataset
 }  // namespace mindspore

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/map_node.h

@@ -93,6 +93,15 @@ class MapNode : public DatasetNode {
   /// \return Status of the function
   Status to_json(nlohmann::json *out_json) override;
 
+  /// \brief Base-class override for GetDatasetSize
+  /// \param[in] size_getter Shared pointer to DatasetSizeGetter
+  /// \param[in] estimate This is only supported by some of the ops and it's used to speed up the process of getting
+  ///     dataset size at the expense of accuracy.
+  /// \param[out] dataset_size the size of the dataset
+  /// \return Status of the function
+  Status GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &size_getter, bool estimate,
+                        int64_t *dataset_size) override;
+
  private:
   std::vector<std::shared_ptr<TensorOperation>> operations_;
   std::vector<std::string> input_columns_;

mindspore/ccsrc/minddata/dataset/engine/ir/datasetops/source/tf_record_node.cc

@@ -171,7 +171,8 @@ Status TFRecordNode::GetDatasetSize(const std::shared_ptr<DatasetSizeGetter> &si
   }
   int64_t num_rows;
   constexpr int64_t kThreadCount = 8;
-  if (!shard_equal_rows_) {
+  // By default, TFRecord will do file-based sharding. But when cache is injected, it will be row-based sharding.
+  if (!shard_equal_rows_ && !IsCached()) {
     // Data will be sharded by file
     std::vector<std::string> shard_file_list;
     RETURN_IF_NOT_OK(GetShardFileList(&shard_file_list));

tests/ut/python/cachetests/cachetest_py.sh

@@ -130,6 +130,9 @@ HandleRcExit $? 0 0
 PytestCmd "test_cache_map.py" "test_cache_map_nested_repeat"
 HandleRcExit $? 0 0
 
+PytestCmd "test_cache_map.py" "test_cache_map_dataset_size" 1
+HandleRcExit $? 0 0
+
 GetSession
 HandleRcExit $? 1 1
 export SESSION_ID=$session_id
@@ -334,6 +337,9 @@ HandleRcExit $? 0 0
 PytestCmd "test_cache_nomap.py" "test_cache_nomap_pyfunc" 1
 HandleRcExit $? 0 0
 
+PytestCmd "test_cache_nomap.py" "test_cache_nomap_dataset_size" 1
+HandleRcExit $? 0 0
+
 GetSession
 HandleRcExit $? 1 1
 export SESSION_ID=$session_id

tests/ut/python/dataset/test_cache_map.py

@@ -2227,6 +2227,76 @@ def test_cache_map_interrupt_and_rerun():
     logger.info("test_cache_map_interrupt_and_rerun Ended.\n")
 
 
+@pytest.mark.skipif(os.environ.get('RUN_CACHE_TEST') != 'TRUE', reason="Require to bring up cache server")
+def test_cache_map_dataset_size1():
+    """
+    Test get_dataset_size() when cache is injected directly after a mappable leaf
+
+       Cache
+         |
+      CelebA
+    """
+
+    logger.info("Test cache map dataset size 1")
+    if "SESSION_ID" in os.environ:
+        session_id = int(os.environ['SESSION_ID'])
+    else:
+        raise RuntimeError("Testcase requires SESSION_ID environment variable")
+
+    some_cache = ds.DatasetCache(session_id=session_id, size=0)
+
+    # This dataset has 4 records
+    ds1 = ds.CelebADataset(CELEBA_DATA_DIR, num_shards=3, shard_id=0, cache=some_cache)
+
+    dataset_size = ds1.get_dataset_size()
+    assert dataset_size == 2
+
+    num_iter = 0
+    for _ in ds1.create_dict_iterator():
+        num_iter += 1
+
+    logger.info("Number of data in ds1: {} ".format(num_iter))
+    assert num_iter == dataset_size
+    logger.info("test_cache_map_dataset_size1 Ended.\n")
+
+
+@pytest.mark.skipif(os.environ.get('RUN_CACHE_TEST') != 'TRUE', reason="Require to bring up cache server")
+def test_cache_map_dataset_size2():
+    """
+    Test get_dataset_size() when cache is injected after map
+
+       Cache
+         |
+    Map(resize)
+         |
+     CelebA
+    """
+
+    logger.info("Test cache map dataset size 2")
+    if "SESSION_ID" in os.environ:
+        session_id = int(os.environ['SESSION_ID'])
+    else:
+        raise RuntimeError("Testcase requires SESSION_ID environment variable")
+
+    some_cache = ds.DatasetCache(session_id=session_id, size=0)
+
+    # This dataset has 4 records
+    ds1 = ds.CelebADataset(CELEBA_DATA_DIR, shuffle=False, decode=True, num_shards=3, shard_id=0)
+    resize_op = c_vision.Resize((224, 224))
+    ds1 = ds1.map(operations=resize_op, input_columns=["image"], cache=some_cache)
+
+    dataset_size = ds1.get_dataset_size()
+    assert dataset_size == 2
+
+    num_iter = 0
+    for _ in ds1.create_dict_iterator():
+        num_iter += 1
+
+    logger.info("Number of data in ds1: {} ".format(num_iter))
+    assert num_iter == dataset_size
+    logger.info("test_cache_map_dataset_size2 Ended.\n")
+
+
 if __name__ == '__main__':
     # This is just a list of tests, don't try to run these tests with 'python test_cache_map.py'
     # since cache server is required to be brought up first
@@ -2285,3 +2355,5 @@ if __name__ == '__main__':
     test_cache_map_python_sampler1()
     test_cache_map_python_sampler2()
     test_cache_map_nested_repeat()
+    test_cache_map_dataset_size1()
+    test_cache_map_dataset_size2()

tests/ut/python/dataset/test_cache_nomap.py

@@ -2355,6 +2355,76 @@ def test_cache_nomap_all_rows_cached():
     logger.info("test_cache_nomap_all_rows_cached Ended.\n")
 
 
+@pytest.mark.skipif(os.environ.get('RUN_CACHE_TEST') != 'TRUE', reason="Require to bring up cache server")
+def test_cache_nomap_dataset_size1():
+    """
+    Test get_dataset_size() when cache is injected directly after a non-mappable leaf
+
+       Cache
+         |
+      TFRecord
+    """
+
+    logger.info("Test cache nomap dataset size 1")
+    if "SESSION_ID" in os.environ:
+        session_id = int(os.environ['SESSION_ID'])
+    else:
+        raise RuntimeError("Testcase requires SESSION_ID environment variable")
+
+    some_cache = ds.DatasetCache(session_id=session_id, size=0)
+
+    # This dataset has 3 records in it only
+    ds1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, num_shards=2, shard_id=0, cache=some_cache)
+
+    dataset_size = ds1.get_dataset_size()
+    assert dataset_size == 2
+
+    num_iter = 0
+    for _ in ds1.create_dict_iterator():
+        num_iter += 1
+
+    logger.info("Number of data in ds1: {} ".format(num_iter))
+    assert num_iter == dataset_size
+    logger.info("test_cache_nomap_dataset_size1 Ended.\n")
+
+
+@pytest.mark.skipif(os.environ.get('RUN_CACHE_TEST') != 'TRUE', reason="Require to bring up cache server")
+def test_cache_nomap_dataset_size2():
+    """
+    Test get_dataset_size() when cache is injected after map
+
+       Cache
+         |
+    Map(decode)
+         |
+     TFRecord
+    """
+
+    logger.info("Test cache nomap dataset size 2")
+    if "SESSION_ID" in os.environ:
+        session_id = int(os.environ['SESSION_ID'])
+    else:
+        raise RuntimeError("Testcase requires SESSION_ID environment variable")
+
+    some_cache = ds.DatasetCache(session_id=session_id, size=0)
+
+    # This dataset has 3 records in it only
+    ds1 = ds.TFRecordDataset(DATA_DIR, SCHEMA_DIR, num_shards=2, shard_id=0)
+    decode_op = c_vision.Decode()
+    ds1 = ds1.map(operations=decode_op, input_columns=["image"], cache=some_cache)
+
+    dataset_size = ds1.get_dataset_size()
+    assert dataset_size == 2
+
+    num_iter = 0
+    for _ in ds1.create_dict_iterator():
+        num_iter += 1
+
+    logger.info("Number of data in ds1: {} ".format(num_iter))
+    assert num_iter == dataset_size
+    logger.info("test_cache_nomap_dataset_size2 Ended.\n")
+
+
 if __name__ == '__main__':
     # This is just a list of tests, don't try to run these tests with 'python test_cache_nomap.py'
     # since cache server is required to be brought up first
@@ -2414,3 +2484,5 @@ if __name__ == '__main__':
     test_cache_nomap_pyfunc_lambda()
     test_cache_nomap_pyfunc_builtin()
     test_cache_nomap_pyfunc_function()
+    test_cache_nomap_dataset_size1()
+    test_cache_nomap_dataset_size2()