tfdatasets
Create efficient and fast data loading pipelines
Creating Datasets
Function(s) | Description |
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text_line_dataset() | A dataset comprising lines from one or more text files. |
tfrecord_dataset() | A dataset comprising records from one or more TFRecord files. |
sql_record_spec() sql_dataset() sqlite_dataset() | A dataset consisting of the results from a SQL query |
tensors_dataset() | Creates a dataset with a single element, comprising the given tensors. |
tensor_slices_dataset() | Creates a dataset whose elements are slices of the given tensors. |
sparse_tensor_slices_dataset() | Splits each rank-N tf$SparseTensor in this dataset row-wise. |
fixed_length_record_dataset() | A dataset of fixed-length records from one or more binary files. |
file_list_dataset() | A dataset of all files matching a pattern |
range_dataset() | Creates a dataset of a step-separated range of values. |
read_files() | Read a dataset from a set of files |
delim_record_spec() csv_record_spec() tsv_record_spec() | Specification for reading a record from a text file with delimited values |
make_csv_dataset() | Reads CSV files into a batched dataset |
Transforming Datasets
Function(s) | Description |
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dataset_map() | Map a function across a dataset. |
dataset_map_and_batch() | Fused implementation of dataset_map() and dataset_batch() |
dataset_prepare() | Prepare a dataset for analysis |
dataset_skip() | Creates a dataset that skips count elements from this dataset |
dataset_filter() | Filter a dataset by a predicate |
dataset_shard() | Creates a dataset that includes only 1 / num_shards of this dataset. |
dataset_shuffle() | Randomly shuffles the elements of this dataset. |
dataset_shuffle_and_repeat() | Shuffles and repeats a dataset returning a new permutation for each epoch. |
dataset_prefetch() | Creates a Dataset that prefetches elements from this dataset. |
dataset_batch() | Combines consecutive elements of this dataset into batches. |
dataset_repeat() | Repeats a dataset count times. |
dataset_cache() | Caches the elements in this dataset. |
dataset_take() | Creates a dataset with at most count elements from this dataset |
dataset_flat_map() | Maps map_func across this dataset and flattens the result. |
dataset_padded_batch() | Combines consecutive elements of this dataset into padded batches. |
dataset_decode_delim() | Transform a dataset with delimted text lines into a dataset with named |
columns | |
dataset_concatenate() | Creates a dataset by concatenating given dataset with this dataset. |
dataset_interleave() | Maps map_func across this dataset, and interleaves the results |
dataset_prefetch_to_device() | A transformation that prefetches dataset values to the given device |
dataset_window() | Combines input elements into a dataset of windows. |
dataset_collect() | Collects a dataset |
zip_datasets() | Creates a dataset by zipping together the given datasets. |
sample_from_datasets() | Samples elements at random from the datasets in datasets . |
with_dataset() | Execute code that traverses a dataset |
Dataset Properites
Function(s) | Description |
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output_types() output_shapes() | Output types and shapes |
output_types() output_shapes() | Output types and shapes |
Dataset Iterators
Function(s) | Description |
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input_fn.tf_dataset() | Construct a tfestimators input function from a dataset |
make_iterator_one_shot() make_iterator_initializable() make_iterator_from_structure() make_iterator_from_string_handle() | Creates an iterator for enumerating the elements of this dataset. |
iterator_get_next() | Get next element from iterator |
iterator_initializer() | An operation that should be run to initialize this iterator. |
iterator_string_handle() | String-valued tensor that represents this iterator |
iterator_make_initializer() | Create an operation that can be run to initialize this iterator |
until_out_of_range() out_of_range_handler() | Execute code that traverses a dataset until an out of range condition occurs |
next_batch() | Tensor(s) for retrieving the next batch from a dataset |
Feature Spec API
Function(s) | Description |
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feature_spec() | Creates a feature specification. |
dense_features() | Dense Features |
dataset_use_spec() | Transform the dataset using the provided spec. |
fit( |
Fits a feature specification. |
scaler | List of pre-made scalers |
scaler_min_max() | Creates an instance of a min max scaler |
scaler_standard() | Creates an instance of a standard scaler |
step_bucketized_column() | Creates bucketized columns |
step_categorical_column_with_hash_bucket() | Creates a categorical column with hash buckets specification |
step_categorical_column_with_identity() | Create a categorical column with identity |
step_categorical_column_with_vocabulary_file() | Creates a categorical column with vocabulary file |
step_categorical_column_with_vocabulary_list() | Creates a categorical column specification |
step_crossed_column() | Creates crosses of categorical columns |
step_embedding_column() | Creates embeddings columns |
step_indicator_column() | Creates Indicator Columns |
step_numeric_column() | Creates a numeric column specification |
step_remove_column() | Creates a step that can remove columns |
step_shared_embeddings_column() | Creates shared embeddings for categorical columns |
steps | Steps for feature columns specification. |
all_nominal() | Find all nominal variables. |
all_numeric() | Speciy all numeric variables. |
has_type() | Identify the type of the variable. |
cur_info_env | Selectors |
layer_input_from_dataset() | Creates a list of inputs from a dataset |
Data
Function(s) | Description |
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hearts | Heart Disease Data Set |