def __init__(self, filenames, compression_type=None, buffer_size=None): """Creates a `TFRecordDataset`. Args: filenames: A `tf.string` tensor containing one or more filenames. compression_type: (Optional.) A `tf.string` scalar evaluating to one of `""` (no compression), `"ZLIB"`, or `"GZIP"`. buffer_size: (Optional.) A `tf.int64` scalar representing the number of bytes in the read buffer. 0 means no buffering. """ # Force the type to string even if filenames is an empty list. self._filenames = ops.convert_to_tensor( filenames, dtypes.string, name="filenames") self._compression_type = convert.optional_param_to_tensor( "compression_type", compression_type, argument_default="", argument_dtype=dtypes.string) self._buffer_size = convert.optional_param_to_tensor( "buffer_size", buffer_size, argument_default=_DEFAULT_READER_BUFFER_SIZE_BYTES) variant_tensor = gen_dataset_ops.tf_record_dataset( self._filenames, self._compression_type, self._buffer_size) super(_TFRecordDataset, self).__init__(variant_tensor)
def __init__(self, filenames, compression_type=None, buffer_size=None, name=None): """Creates a `TFRecordDataset`. Args: filenames: A `tf.string` tensor containing one or more filenames. compression_type: (Optional.) A `tf.string` scalar evaluating to one of `""` (no compression), `"ZLIB"`, or `"GZIP"`. buffer_size: (Optional.) A `tf.int64` scalar representing the number of bytes in the read buffer. 0 means no buffering. name: (Optional.) A name for the tf.data operation. """ self._filenames = filenames self._compression_type = convert.optional_param_to_tensor( "compression_type", compression_type, argument_default="", argument_dtype=dtypes.string) self._buffer_size = convert.optional_param_to_tensor( "buffer_size", buffer_size, argument_default=_DEFAULT_READER_BUFFER_SIZE_BYTES) self._name = name variant_tensor = gen_dataset_ops.tf_record_dataset( self._filenames, self._compression_type, self._buffer_size, metadata=self._metadata.SerializeToString()) super(_TFRecordDataset, self).__init__(variant_tensor)
def _as_variant_tensor(self): return gen_dataset_ops.tf_record_dataset( self._filenames, self._compression_type, self._buffer_size)