Functional API

Quick start

Warning

This API is experimental and subject to change without notice!

Functional API is designed to simplify the usage of DALI operators in a psuedo-imperative way. It exposes operators as functions, with ths same name as the operator class, but converted to snake_case - for example ops.FileReader will be exposed as fn.file_reader().

Example:

import nvidia.dali as dali

pipe = dali.pipeline.Pipeline(batch_size = 3, num_threads = 2, device_id = 0)
with pipe:
    files, labels = dali.fn.file_reader(file_root = "./my_file_root")
    images = dali.fn.image_decoder(files, device = "mixed")
    images = dali.fn.rotate(images, angle = dali.fn.uniform(range=(-45,45)))
    images = dali.fn.resize(images, resize_x = 300, resize_y = 300)
    pipe.set_outputs(images, labels)

pipe.build()
outputs = pipe.run()

The use of functional API does not change other aspects of pipeline definition - the functions still operate on and return pipeline.DataNode objects.

Interoperability with operator objects

Functional API is, for the major part, only a wrapper around operator objects - as such, it is inherently compatible with the object-based API. The following example mixes the two, using object API to pre-configure a file reader and a resize operator:

pipe = dali.pipeline.Pipeline(batch_size = 3, num_threads = 2, device_id = 0)
reader = dali.ops.FileReader(file_root = ".")
resize = dali.ops.Resize(device = "gpu", resize_x = 300, resize_y = 300)

with pipe:
    files, labels = reader()
    images = dali.fn.image_decoder(files, device = "mixed")
    images = dali.fn.rotate(images, angle = dali.fn.uniform(range=(-45,45)))
    images = resize(images)
    pipe.set_outputs(images, labels)

pipe.build()
outputs = pipe.run()

Functions

nvidia.dali.fn.audio_decoder(*inputs, **arguments)

see nvidia.dali.ops.AudioDecoder

nvidia.dali.fn.bb_flip(*inputs, **arguments)

see nvidia.dali.ops.BbFlip

nvidia.dali.fn.bbox_paste(*inputs, **arguments)

see nvidia.dali.ops.BBoxPaste

nvidia.dali.fn.box_encoder(*inputs, **arguments)

see nvidia.dali.ops.BoxEncoder

nvidia.dali.fn.brightness(*inputs, **arguments)

see nvidia.dali.ops.Brightness

nvidia.dali.fn.brightness_contrast(*inputs, **arguments)

see nvidia.dali.ops.BrightnessContrast

nvidia.dali.fn.caffe2_reader(*inputs, **arguments)

see nvidia.dali.ops.Caffe2Reader

nvidia.dali.fn.caffe_reader(*inputs, **arguments)

see nvidia.dali.ops.CaffeReader

nvidia.dali.fn.cast(*inputs, **arguments)

see nvidia.dali.ops.Cast

nvidia.dali.fn.coco_reader(*inputs, **arguments)

see nvidia.dali.ops.COCOReader

nvidia.dali.fn.coin_flip(*inputs, **arguments)

see nvidia.dali.ops.CoinFlip

nvidia.dali.fn.color_space_conversion(*inputs, **arguments)

see nvidia.dali.ops.ColorSpaceConversion

nvidia.dali.fn.color_twist(*inputs, **arguments)

see nvidia.dali.ops.ColorTwist

nvidia.dali.fn.constant(*inputs, **arguments)

see nvidia.dali.ops.Constant

nvidia.dali.fn.contrast(*inputs, **arguments)

see nvidia.dali.ops.Contrast

nvidia.dali.fn.coord_flip(*inputs, **arguments)

see nvidia.dali.ops.CoordFlip

nvidia.dali.fn.copy(*inputs, **arguments)

see nvidia.dali.ops.Copy

nvidia.dali.fn.crop(*inputs, **arguments)

see nvidia.dali.ops.Crop

nvidia.dali.fn.crop_mirror_normalize(*inputs, **arguments)

see nvidia.dali.ops.CropMirrorNormalize

nvidia.dali.fn.dl_tensor_python_function(*inputs, **arguments)

see nvidia.dali.ops.DLTensorPythonFunction

nvidia.dali.fn.dump_image(*inputs, **arguments)

see nvidia.dali.ops.DumpImage

nvidia.dali.fn.element_extract(*inputs, **arguments)

see nvidia.dali.ops.ElementExtract

nvidia.dali.fn.erase(*inputs, **arguments)

see nvidia.dali.ops.Erase

nvidia.dali.fn.external_source(source=None, num_outputs=None, *, cycle=None, name=None, device='cpu', layout=None)

Creates a data node which is populated with data from a Python source. The data can be provided by the source function or iterable, or it can be provided by pipeline.feed_input(name, data, layout) inside pipeline.iter_setup.

Note

To return a batch of copies of the same tensor, use nvidia.dali.types.Constant(), which is more performant.

Parameters

• source (callable or iterable) – The source of the data. The source is polled for data (via a call source() or next(source) whenever the pipeline needs input for the next iteration. The source can supply one or more data batches, depending on the value of num_outputs. If num_outputs is not set, the source is expected to return a single batch. If it’s specified, the data is expected to a be tuple or list where each element corresponds to respective return value of the external_source. If the source is a callable and has a positional argument, it is assumed to be the current iteration number and consecutive calls will be source(0), source(1), etc. If the source is a generator function, it is invoked and treated as an iterable - however, unlike a gnerator, it can be used with cycle, in which case the function will be called again when the generator reaches end of iteration.

• num_outputs (int, optional) – If specified, denotes the number of TensorLists produced by the source function

Keyword Arguments

• cycle (bool) – If True, the source will be wrapped. Otherwise, StopIteration will be raised when end of data is reached. This flag requires that source is either a collection, i.e. an iterable object where iter(source) will return a fresh iterator on each call or a generator function. In the latter case, the generator function will be called again when more data is requested than was yielded by the function.

• name (str, optional) – The name of the data node - used when feeding the data in iter_setup; can be omitted if the data is provided by source.

• layout (layout str or list/tuple thereof) – If provided, sets the layout of the data. When num_outputs > 1, layout can be a list containing a distinct layout for each output. If the list has fewer elements than num_outputs, only the first outputs have the layout set, the reset have it cleared.

nvidia.dali.fn.fast_resize_crop_mirror(*inputs, **arguments)

see nvidia.dali.ops.FastResizeCropMirror

nvidia.dali.fn.file_reader(*inputs, **arguments)

see nvidia.dali.ops.FileReader

nvidia.dali.fn.flip(*inputs, **arguments)

see nvidia.dali.ops.Flip

nvidia.dali.fn.hsv(*inputs, **arguments)

see nvidia.dali.ops.Hsv

nvidia.dali.fn.hue(*inputs, **arguments)

see nvidia.dali.ops.Hue

nvidia.dali.fn.image_decoder(*inputs, **arguments)

see nvidia.dali.ops.ImageDecoder

nvidia.dali.fn.image_decoder_crop(*inputs, **arguments)

see nvidia.dali.ops.ImageDecoderCrop

nvidia.dali.fn.image_decoder_random_crop(*inputs, **arguments)

see nvidia.dali.ops.ImageDecoderRandomCrop

nvidia.dali.fn.image_decoder_slice(*inputs, **arguments)

see nvidia.dali.ops.ImageDecoderSlice

nvidia.dali.fn.jitter(*inputs, **arguments)

see nvidia.dali.ops.Jitter

nvidia.dali.fn.lookup_table(*inputs, **arguments)

see nvidia.dali.ops.LookupTable

nvidia.dali.fn.mel_filter_bank(*inputs, **arguments)

see nvidia.dali.ops.MelFilterBank

nvidia.dali.fn.mfc(*inputs, **arguments)

see nvidia.dali.ops.MFCC

nvidia.dali.fn.mxnet_reader(*inputs, **arguments)

see nvidia.dali.ops.MXNetReader

nvidia.dali.fn.nonsilent_region(*inputs, **arguments)

see nvidia.dali.ops.NonsilentRegion

nvidia.dali.fn.normal_distribution(*inputs, **arguments)

see nvidia.dali.ops.NormalDistribution

nvidia.dali.fn.normalize(*inputs, **arguments)

see nvidia.dali.ops.Normalize

nvidia.dali.fn.numpy_reader(*inputs, **arguments)

see nvidia.dali.ops.NumpyReader

nvidia.dali.fn.old_color_twist(*inputs, **arguments)

see nvidia.dali.ops.OldColorTwist

nvidia.dali.fn.one_hot(*inputs, **arguments)

see nvidia.dali.ops.OneHot

nvidia.dali.fn.optical_flow(*inputs, **arguments)

see nvidia.dali.ops.OpticalFlow

nvidia.dali.fn.pad(*inputs, **arguments)

see nvidia.dali.ops.Pad

nvidia.dali.fn.paste(*inputs, **arguments)

see nvidia.dali.ops.Paste

nvidia.dali.fn.power_spectrum(*inputs, **arguments)

see nvidia.dali.ops.PowerSpectrum

nvidia.dali.fn.preemphasis_filter(*inputs, **arguments)

see nvidia.dali.ops.PreemphasisFilter

nvidia.dali.fn.python_function(*inputs, **arguments)

see nvidia.dali.ops.PythonFunction

nvidia.dali.fn.random_bbox_crop(*inputs, **arguments)

see nvidia.dali.ops.RandomBBoxCrop

nvidia.dali.fn.random_resized_crop(*inputs, **arguments)

see nvidia.dali.ops.RandomResizedCrop

nvidia.dali.fn.reinterpret(*inputs, **arguments)

see nvidia.dali.ops.Reinterpret

nvidia.dali.fn.reshape(*inputs, **arguments)

see nvidia.dali.ops.Reshape

nvidia.dali.fn.resize(*inputs, **arguments)

see nvidia.dali.ops.Resize

nvidia.dali.fn.resize_crop_mirror(*inputs, **arguments)

see nvidia.dali.ops.ResizeCropMirror

nvidia.dali.fn.rotate(*inputs, **arguments)

see nvidia.dali.ops.Rotate

nvidia.dali.fn.saturation(*inputs, **arguments)

see nvidia.dali.ops.Saturation

nvidia.dali.fn.sequence_reader(*inputs, **arguments)

see nvidia.dali.ops.SequenceReader

nvidia.dali.fn.sequence_rearrange(*inputs, **arguments)

see nvidia.dali.ops.SequenceRearrange

nvidia.dali.fn.shapes(*inputs, **arguments)

see nvidia.dali.ops.Shapes

nvidia.dali.fn.slice(*inputs, **arguments)

see nvidia.dali.ops.Slice

nvidia.dali.fn.spectrogram(*inputs, **arguments)

see nvidia.dali.ops.Spectrogram

nvidia.dali.fn.sphere(*inputs, **arguments)

see nvidia.dali.ops.Sphere

nvidia.dali.fn.ssd_random_crop(*inputs, **arguments)

see nvidia.dali.ops.SSDRandomCrop

nvidia.dali.fn.tfrecord_reader(*inputs, **arguments)

see nvidia.dali.ops.TFRecordReader

nvidia.dali.fn.to_decibels(*inputs, **arguments)

see nvidia.dali.ops.ToDecibels

nvidia.dali.fn.transpose(*inputs, **arguments)

see nvidia.dali.ops.Transpose

nvidia.dali.fn.uniform(*inputs, **arguments)

see nvidia.dali.ops.Uniform

nvidia.dali.fn.video_reader(*inputs, **arguments)

see nvidia.dali.ops.VideoReader

nvidia.dali.fn.warp_affine(*inputs, **arguments)

see nvidia.dali.ops.WarpAffine

nvidia.dali.fn.water(*inputs, **arguments)

see nvidia.dali.ops.Water