Supported operations

class nvidia.dali.ops.BbFlip(**kwargs)

Operator for horizontal flip (mirror) of bounding box.

Input: Bounding box coordinates; in either [x, y, w, h] or [left, top, right, bottom] format. All coordinates are in the image coordinate system (i.e. 0.0-1.0)

Parameters:

• horizontal (int or int tensor, optional, default = 1) – Perform flip along horizontal axis. Default: 1
• ltrb (bool, optional, default = False) –

  True, for two-point (ltrb).

  False for for width-height representation. Default: False

• vertical (int or int tensor, optional, default = 0) – Perform flip along vertical axis. Default: 0

class nvidia.dali.ops.Brightness(**kwargs)

Changes the brightness of an image

Parameters:

• brightness (float or float tensor, optional, default = 1.0) –

  Brightness change factor. Values >= 0 are accepted. For example:

  • 0 - black image,
  • 1 - no change
  • 2 - increase brightness twice
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image

class nvidia.dali.ops.COCOReader(**kwargs)

Read data from a COCO dataset composed of directory with images

and an anotation files. For each image, with m bboxes, returns its bboxes as (m,4) Tensor (m * [x, y, w, h] or `m * [left, top, right, bottom]`) and labels as (m,1) Tensor (m * category_id).

Parameters:

• annotations_file (str or list of str) – List of paths to the JSON annotations files.
• file_root (str) – Path to a directory containing data files.
• file_list (str, optional, default = '') – Path to the file with a list of pairs file label (leave empty to traverse the file_root directory to obtain files and labels)
• initial_fill (int, optional, default = 1024) – Size of the buffer used for shuffling.
• ltrb (bool, optional, default = False) – If true, bboxes are returned as [left, top, right, bottom], else [x, y, width, height]. Default: False
• num_shards (int, optional, default = 1) – Partition the data into this many parts (used for multiGPU training).
• random_shuffle (bool, optional, default = False) – Whether to randomly shuffle data.
• ratio (bool, optional, default = False) – If true, bboxes returned values as expressed as ratio w.r.t. to the image width and height. Default: False
• shard_id (int, optional, default = 0) – Id of the part to read.
• tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.

class nvidia.dali.ops.Caffe2Reader(**kwargs)

Read sample data from a Caffe2 Lightning Memory-Mapped Database (LMDB).

Parameters:

• path (str) – Path to Caffe2 LMDB directory.
• additional_inputs (int, optional, default = 0) – Additional auxiliary data tensors provided for each sample.
• bbox (bool, optional, default = False) – Denotes if bounding-box information is present.
• initial_fill (int, optional, default = 1024) – Size of the buffer used for shuffling.
• label_type (int, optional, default = 0) –

  Type of label stored in dataset.

  • 0 = SINGLE_LABEL : single integer label for multi-class classification
  • 1 = MULTI_LABEL_SPARSE : sparse active label indices for multi-label classification
  • 2 = MULTI_LABEL_DENSE : dense label embedding vector for label embedding regression
  • 3 = MULTI_LABEL_WEIGHTED_SPARSE : sparse active label indices with per-label weights for multi-label classification.
• num_labels (int, optional, default = 1) – Number of classes in dataset. Required when sparse labels are used.
• num_shards (int, optional, default = 1) – Partition the data into this many parts (used for multiGPU training).
• random_shuffle (bool, optional, default = False) – Whether to randomly shuffle data.
• shard_id (int, optional, default = 0) – Id of the part to read.
• tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.

class nvidia.dali.ops.CaffeReader(**kwargs)

Read (Image, label) pairs from a Caffe LMDB

Parameters:

• path (str) – Path to Caffe LMDB directory.
• initial_fill (int, optional, default = 1024) – Size of the buffer used for shuffling.
• num_shards (int, optional, default = 1) – Partition the data into this many parts (used for multiGPU training).
• random_shuffle (bool, optional, default = False) – Whether to randomly shuffle data.
• shard_id (int, optional, default = 0) – Id of the part to read.
• tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.

class nvidia.dali.ops.Cast(**kwargs)

Cast tensor to a different type

Parameters:dtype (nvidia.dali.types.DALIDataType) – Output data type.

class nvidia.dali.ops.CoinFlip(**kwargs)

Produce tensor filled with 0s and 1s - results of random coin flip, usable as an argument for select ops.

Parameters:probability (float, optional, default = 0.5) – Probability of returning 1.

class nvidia.dali.ops.ColorTwist(**kwargs)

Combination of hue, saturation, contrast and brightness.

Parameters:brightness (float or float tensor, optional, default = 1.0) –

Brightness change factor. Values >= 0 are accepted. For example:

• 0 - black image,
• 1 - no change
• 2 - increase brightness twice

contrast : float or float tensor, optional, default = 1.0

Contrast change factor. Values >= 0 are accepted. For example:

• 0 - gray image,
• 1 - no change
• 2 - increase contrast twice

hue : float or float tensor, optional, default = 0.0

Hue change in angles.

image_type : nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB

The color space of input and output image

saturation : float or float tensor, optional, default = 1.0

Saturation change factor. Values >= 0 are supported. For example:

• 0 - completely desaturated image
• 1 - no change to image’s saturation

class nvidia.dali.ops.Contrast(**kwargs)

Changes the color contrast of the image.

Parameters:

• contrast (float or float tensor, optional, default = 1.0) –

  Contrast change factor. Values >= 0 are accepted. For example:

  • 0 - gray image,
  • 1 - no change
  • 2 - increase contrast twice
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image

class nvidia.dali.ops.Copy(**kwargs)

Make a copy of the input tensor

class nvidia.dali.ops.Crop(**kwargs)

Perform a random crop.

Parameters:

• crop (int or list of int) –

  Size of the cropped image. If only a single value c is provided,

  the resulting crop will be square with size (c,c)

• crop_pos_x (float or float tensor, optional, default = 0.5) – Horizontal position of the crop in image coordinates (0.0 - 1.0)
• crop_pos_y (float or float tensor, optional, default = 0.5) – Vertical position of the crop in image coordinates (0.0 - 1.0)
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image

class nvidia.dali.ops.CropCastPermute(**kwargs)

Perform a random crop, data type cast and permute (from NHWC to NCHW).

Parameters:

• crop (int or list of int) –

  Size of the cropped image. If only a single value c is provided,

  the resulting crop will be square with size (c,c)

• crop_pos_x (float or float tensor, optional, default = 0.5) – Horizontal position of the crop in image coordinates (0.0 - 1.0)
• crop_pos_y (float or float tensor, optional, default = 0.5) – Vertical position of the crop in image coordinates (0.0 - 1.0)
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image
• output_dtype (nvidia.dali.types.DALIDataType, optional, default = DALIDataType.FLOAT) –

  Output data type. If NO_TYPE is specified, the ouput data type is inferred

  from the input data type.

• output_layout (nvidia.dali.types.DALITensorLayout, optional, default = DALITensorLayout.NCHW) – Output tensor data layout

class nvidia.dali.ops.CropMirrorNormalize(**kwargs)

Perform fused cropping, normalization, format conversion (NHWC to NCHW) if desired, and type casting. Normalization takes input image and produces output using formula

output = (input - mean) / std

Parameters:

• crop (int or list of int) – Size of the cropped image. If only a single value c is provided, the resulting crop will be square with size (c,c)
• mean (float or list of float) – Mean pixel values for image normalization.
• std (float or list of float) – Standard deviation values for image normalization.
• crop_pos_x (float or float tensor, optional, default = 0.5) – Horizontal position of the crop in image coordinates (0.0 - 1.0).
• crop_pos_y (float or float tensor, optional, default = 0.5) – Vertical position of the crop in image coordinates (0.0 - 1.0).
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image.
• mirror (int or int tensor, optional, default = 0) –

  Mask for horizontal flip.

  • 0 - do not perform horizontal flip for this image
  • 1 - perform horizontal flip for this image.
• output_dtype (nvidia.dali.types.DALIDataType, optional, default = DALIDataType.FLOAT) – Output data type.
• output_layout (nvidia.dali.types.DALITensorLayout, optional, default = DALITensorLayout.NCHW) – Output tensor data layout
• pad_output (bool, optional, default = False) – Whether to pad the output to number of channels being multiple of 4.

class nvidia.dali.ops.DummyOp(**kwargs)

Dummy operator for testing

Parameters:num_outputs (int, optional, default = 2) – Number of outputs.

class nvidia.dali.ops.DumpImage(**kwargs)

Save images in batch to disk in PPM format. Useful for debugging.

Parameters:

• input_layout (nvidia.dali.types.DALITensorLayout, optional, default = DALITensorLayout.NHWC) – Layout of input images.
• suffix (str, optional, default = '') – Suffix to be added to output file names.

class nvidia.dali.ops.ExternalSource(**kwargs)

Allows externally provided data to be passed as an input to the pipeline,

see nvidia.dali.pipeline.Pipeline.feed_input() and nvidia.dali.pipeline.Pipeline.iter_setup(). Currenlty this operator is not supported in TensorFlow.

class nvidia.dali.ops.FastResizeCropMirror(**kwargs)

Perform a fused resize, crop, mirror operation. Handles both fixed and random resizing and cropping. Backprojects the desired crop through the resize operation to reduce the amount of work performed.

Parameters:

• crop (int or list of int) – Size of the cropped image. If only a single value c is provided, the resulting crop will be square with size (c,c)
• crop_pos_x (float or float tensor, optional, default = 0.5) – Horizontal position of the crop in image coordinates (0.0 - 1.0).
• crop_pos_y (float or float tensor, optional, default = 0.5) – Vertical position of the crop in image coordinates (0.0 - 1.0).
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_LINEAR) – Type of interpolation used.
• mirror (int or int tensor, optional, default = 0) –

  Mask for horizontal flip.

  • 0 - do not perform horizontal flip for this image
  • 1 - perform horizontal flip for this image.
• resize_shorter (float or float tensor, optional, default = 0.0) – The length of the shorter dimension of the resized image. This option is mutually exclusive with resize_x and resize_y. The op will keep the aspect ratio of the original image.
• resize_x (float or float tensor, optional, default = 0.0) – The length of the X dimension of the resized image. This option is mutually exclusive with resize_shorter. If the resize_y is left at 0, then the op will keep the aspect ratio of the original image.
• resize_y (float or float tensor, optional, default = 0.0) – The length of the Y dimension of the resized image. This option is mutually exclusive with resize_shorter. If the resize_x is left at 0, then the op will keep the aspect ratio of the original image.

class nvidia.dali.ops.FileReader(**kwargs)

Read (Image, label) pairs from a directory

Parameters:

• file_root (str) – Path to a directory containing data files.
• file_list (str, optional, default = '') – Path to the file with a list of pairs file label (leave empty to traverse the file_root directory to obtain files and labels)
• initial_fill (int, optional, default = 1024) – Size of the buffer used for shuffling.
• num_shards (int, optional, default = 1) – Partition the data into this many parts (used for multiGPU training).
• random_shuffle (bool, optional, default = False) – Whether to randomly shuffle data.
• shard_id (int, optional, default = 0) – Id of the part to read.
• tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.

class nvidia.dali.ops.Flip(**kwargs)

Flip the image on the horizontal and/or vertical axes.

Parameters:

• fill_value (float, optional, default = 0.0) – Color value used for padding pixels.
• horizontal (int or int tensor, optional, default = 1) – Perform a horizontal flip. Default value is 1.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_NN) – Type of interpolation used.
• mask (int or int tensor, optional, default = 1) –

  Whether to apply this augmentation to the input image.

  • 0 - do not apply this transformation
  • 1 - apply this transformation
• vertical (int or int tensor, optional, default = 0) – Perform a vertical flip. Default value is 0.

class nvidia.dali.ops.HostDecoder(**kwargs)

Decode images on the host using OpenCV. When applicable, it will pass execution to faster, format-specific decoders (like libjpeg-turbo). Output of the decoder is in HWC ordering.

Parameters:output_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of output image.

class nvidia.dali.ops.Hue(**kwargs)

Changes the hue level of the image.

Parameters:

• hue (float or float tensor, optional, default = 0.0) – Hue change in angles.
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image

class nvidia.dali.ops.Jitter(**kwargs)

Perform a random Jitter augmentation. The output image is produced by moving each pixel by a random amount bounded by half of nDegree parameter (in both x and y dimensions).

Parameters:

• fill_value (float, optional, default = 0.0) – Color value used for padding pixels.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_NN) – Type of interpolation used.
• mask (int or int tensor, optional, default = 1) –

  Whether to apply this augmentation to the input image.

  • 0 - do not apply this transformation
  • 1 - apply this transformation
• nDegree (int, optional, default = 2) – Each pixel is moved by a random amount in range [-nDegree/2, nDegree/2].

class nvidia.dali.ops.MXNetReader(**kwargs)

Read sample data from a MXNet RecordIO

Parameters:

• index_path (str or list of str) – List (of length 1) containing a path to index (.idx) file. It is generated by the MXNet’s im2rec.py script together with RecordIO file. It can also be generated using rec2idx script distributed with DALI.
• path (str or list of str) – List of paths to RecordIO files.
• initial_fill (int, optional, default = 1024) – Size of the buffer used for shuffling.
• num_shards (int, optional, default = 1) – Partition the data into this many parts (used for multiGPU training).
• random_shuffle (bool, optional, default = False) – Whether to randomly shuffle data.
• shard_id (int, optional, default = 0) – Id of the part to read.
• tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.

class nvidia.dali.ops.NormalizePermute(**kwargs)

Perform fused normalization, format conversion from NHWC to NCHW and type casting. Normalization takes input image and produces output using formula

output = (input - mean) / std

Parameters:

• height (int) – Height of the input image.
• mean (float or list of float) – Mean pixel values for image normalization.
• std (float or list of float) – Standard deviation values for image normalization.
• width (int) – Width of the input image.
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image.
• output_dtype (nvidia.dali.types.DALIDataType, optional, default = DALIDataType.FLOAT) – Output data type.

class nvidia.dali.ops.Paste(**kwargs)

Paste the input image on a larger canvas. The canvas size is equal to input size * ratio.

Parameters:

• fill_value (int or list of int) –

  Tuple of values of the color to fill the canvas.

  Length of the tuple needs to be equal to n_channels.

• ratio (float or float tensor) – Ratio of canvas size to input size, must be > 1.
• n_channels (int, optional, default = 3) – Number of channels in the image.
• paste_x (float or float tensor, optional, default = 0.5) – Horizontal position of the paste in image coordinates (0.0 - 1.0)
• paste_y (float or float tensor, optional, default = 0.5) – Vertical position of the paste in image coordinates (0.0 - 1.0)

class nvidia.dali.ops.RandomResizedCrop(**kwargs)

Perform a crop with randomly chosen area and aspect ratio, then resize it to given size.

Parameters:

• size (int or list of int) – Size of resized image.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_LINEAR) – Type of interpolation used.
• num_attempts (int, optional, default = 10) – Maximum number of attempts used to choose random area and aspect ratio.
• random_area (float or list of float, optional, default = [0.08, 1.0]) – Range from which to choose random area factor A. Before resizing, the cropped image’s area will be equal to A * original image’s area.
• random_aspect_ratio (float or list of float, optional, default = [0.75, 1.333333]) – Range from which to choose random aspect ratio.

class nvidia.dali.ops.Resize(**kwargs)

Resize images.

Parameters:

• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_LINEAR) – Type of interpolation used.
• resize_shorter (float or float tensor, optional, default = 0.0) – The length of the shorter dimension of the resized image. This option is mutually exclusive with resize_x and resize_y. The op will keep the aspect ratio of the original image.
• resize_x (float or float tensor, optional, default = 0.0) – The length of the X dimension of the resized image. This option is mutually exclusive with resize_shorter. If the resize_y is left at 0, then the op will keep the aspect ratio of the original image.
• resize_y (float or float tensor, optional, default = 0.0) – The length of the Y dimension of the resized image. This option is mutually exclusive with resize_shorter. If the resize_x is left at 0, then the op will keep the aspect ratio of the original image.
• save_attrs (bool, optional, default = False) – Save reshape attributes for testing.

class nvidia.dali.ops.ResizeCropMirror(**kwargs)

Perform a fused resize, crop, mirror operation. Handles both fixed and random resizing and cropping.

Parameters:

• crop (int or list of int) – Size of the cropped image. If only a single value c is provided, the resulting crop will be square with size (c,c)
• crop_pos_x (float or float tensor, optional, default = 0.5) – Horizontal position of the crop in image coordinates (0.0 - 1.0).
• crop_pos_y (float or float tensor, optional, default = 0.5) – Vertical position of the crop in image coordinates (0.0 - 1.0).
• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_LINEAR) – Type of interpolation used.
• mirror (int or int tensor, optional, default = 0) –

  Mask for horizontal flip.

  • 0 - do not perform horizontal flip for this image
  • 1 - perform horizontal flip for this image.
• resize_shorter (float or float tensor, optional, default = 0.0) – The length of the shorter dimension of the resized image. This option is mutually exclusive with resize_x and resize_y. The op will keep the aspect ratio of the original image.
• resize_x (float or float tensor, optional, default = 0.0) – The length of the X dimension of the resized image. This option is mutually exclusive with resize_shorter. If the resize_y is left at 0, then the op will keep the aspect ratio of the original image.
• resize_y (float or float tensor, optional, default = 0.0) – The length of the Y dimension of the resized image. This option is mutually exclusive with resize_shorter. If the resize_x is left at 0, then the op will keep the aspect ratio of the original image.

class nvidia.dali.ops.Rotate(**kwargs)

Rotate the image.

Parameters:

• angle (float or float tensor) – Rotation angle.
• fill_value (float, optional, default = 0.0) – Color value used for padding pixels.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_NN) – Type of interpolation used.
• mask (int or int tensor, optional, default = 1) –

  Whether to apply this augmentation to the input image.

  • 0 - do not apply this transformation
  • 1 - apply this transformation

class nvidia.dali.ops.SSDRandomCrop(**kwargs)

Perform a random crop with bounding boxes where IoU meets randomly selected threshold between 0-1. When IoU falls below threshold new random crop is generated up to num_attempts. As an input, it accepts image, bounding boxes and labels. At the output cropped image, cropped and valid bounding boxes and valid labels are returned.

Parameters:num_attempts (int, optional, default = 1) – Number of attempts, the default value is 1.

class nvidia.dali.ops.Saturation(**kwargs)

Changes saturation level of the image.

Parameters:

• image_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of input and output image
• saturation (float or float tensor, optional, default = 1.0) –

  Saturation change factor. Values >= 0 are supported. For example:

  • 0 - completely desaturated image
  • 1 - no change to image’s saturation

class nvidia.dali.ops.Sphere(**kwargs)

Perform a sphere augmentation.

Parameters:

• fill_value (float, optional, default = 0.0) – Color value used for padding pixels.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_NN) – Type of interpolation used.
• mask (int or int tensor, optional, default = 1) –

  Whether to apply this augmentation to the input image.

  • 0 - do not apply this transformation
  • 1 - apply this transformation

class nvidia.dali.ops.TFRecordReader(path, index_path, features, **kwargs)

Read sample data from a TensorFlow TFRecord file.

Parameters:

• features (dict of (string, nvidia.dali.tfrecord.Feature)) – Dictionary of names and configuration of features existing in TFRecord file. Typically obtained using helper functions dali.tfrecord.FixedLenFeature and dali.tfrecord.VarLenFeature, they are equivalent to TensorFlow’s tf.FixedLenFeature and tf.VarLenFeature respectively.
• index_path (str or list of str) – List of paths to index files (1 index file for every TFRecord file). Index files may be obtained from TFRecord files using tfrecord2idx script distributed with DALI.
• path (str or list of str) – List of paths to TFRecord files.
• initial_fill (int, optional, default = 1024) – Size of the buffer used for shuffling.
• num_shards (int, optional, default = 1) – Partition the data into this many parts (used for multiGPU training).
• random_shuffle (bool, optional, default = False) – Whether to randomly shuffle data.
• shard_id (int, optional, default = 0) – Id of the part to read.
• tensor_init_bytes (int, optional, default = 1048576) – Hint for how much memory to allocate per image.

class nvidia.dali.ops.Uniform(**kwargs)

Produce tensor filled with uniformly distributed random numbers.

Parameters:range (float or list of float, optional, default = [-1.0, 1.0]) – Range of produced random numbers.

class nvidia.dali.ops.WarpAffine(**kwargs)

Apply an affine transformation to the image.

Parameters:

• matrix (float or list of float) –

  Matrix of the transform (dst -> src). Given list of values (M11, M12, M13, M21, M22, M23) this operation will produce a new image using formula

  dst(x,y) = src(M11 * x + M12 * y + M13, M21 * x + M22 * y + M23)

  It is equivalent to OpenCV’s warpAffine operation with a flag WARP_INVERSE_MAP set.

• fill_value (float, optional, default = 0.0) – Color value used for padding pixels.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_NN) – Type of interpolation used.
• mask (int or int tensor, optional, default = 1) –

  Whether to apply this augmentation to the input image.

  • 0 - do not apply this transformation
  • 1 - apply this transformation
• use_image_center (bool, optional, default = False) – Whether to use image center as the center of transformation. When this is True coordinates are calculated from the center of the image.

class nvidia.dali.ops.Water(**kwargs)

Perform a water augmentation (make image appear to be underwater).

Parameters:

• ampl_x (float, optional, default = 10.0) – Amplitude of the wave in x direction.
• ampl_y (float, optional, default = 10.0) – Amplitude of the wave in y direction.
• fill_value (float, optional, default = 0.0) – Color value used for padding pixels.
• freq_x (float, optional, default = 0.049087) – Frequency of the wave in x direction.
• freq_y (float, optional, default = 0.049087) – Frequence of the wave in y direction.
• interp_type (nvidia.dali.types.DALIInterpType, optional, default = DALIInterpType.INTERP_NN) – Type of interpolation used.
• mask (int or int tensor, optional, default = 1) –

  Whether to apply this augmentation to the input image.

  • 0 - do not apply this transformation
  • 1 - apply this transformation
• phase_x (float, optional, default = 0.0) – Phase of the wave in x direction.
• phase_y (float, optional, default = 0.0) – Phase of the wave in y direction.

class nvidia.dali.ops.nvJPEGDecoder(**kwargs)

Decode JPEG images using the nvJPEG library. Output of the decoder is on the GPU and uses HWC ordering.

Parameters:

• device_memory_padding (int, optional, default = 16777216) – Padding for nvJPEG’s device memory allocations.
• host_memory_padding (int, optional, default = 16777216) – Padding for nvJPEG’s host memory allocations.
• output_type (nvidia.dali.types.DALIImageType, optional, default = DALIImageType.RGB) – The color space of output image.
• use_batched_decode (bool, optional, default = False) – Use nvJPEG’s batched decoding API.