dragon

Classes

class DeviceSpec : Describe a computation device.

class GradientTape : Record the operations for auto differentiation.

class Tensor : A multi-dimensional array for computation

class Workspace : Standalone environment for resources and computations.

Functions

argsort(…) : Return the index of sorted elements along the given axis.

assign(…) : Assign the value to input.

boolean_mask(…) : Return the elements of input where mask is true.

broadcast_to(…) : Broadcast input according to a given shape.

cast(…) : Cast the data type of input.

channel_affine(…) : Apply affine transformation to each channel of input.

channel_normalize(…) : Apply normalization to each channel of input.

channel_shuffle(…) : Apply group shuffle to each channel of input. [Zhang et.al, 2017].

concat(…) : Concatenate the inputs along the given axis.

constant(…) : Return a tensor initialized from the value.

device(…) : Context-manager to nest the device spec.

eager_mode(…) : Context-manager set the eager execution mode.

variable_scope(…) : Context-manager to nest the namespace for variables.

expand_dims(…) : Expand the dimensions of input with size 1.

eye(…) : Return a tensor constructed as the identity matrix.

eye_like(…) :Return a tensor of identity matrix with shape as the other.

fill(…) : Return a tensor filled with the scalar value.

flatten(…) : Flatten the input along the given axes.

function(…) : Compile a function and return an executable.

gather(…) : Gather elements along the given axis using index.

gather_elements(…) : Gather elements along the given axis of index.

get_num_threads(…) : Return the number of threads for cpu parallelism.

get_workspace(…) : Return the default workspace.

graph_mode(…) : Context-manager set the graph execution mode.

identity(…) : Return a tensor copied from the input.

linspace(…) : Generate evenly spaced values within intervals along the given axis.

load_library(…) : Load a shared library.

name_scope(…) : Context-manager to nest the name as prefix for operations.

nonzero(…) : Return the index of non-zero elements.

ones(…) : Return a tensor filled with ones.

ones_like(…) : Return a tensor of ones with shape as the other.

one_hot(…) : Return the one-hot representation for input.

pad(…) : Pad the input according to the given sizes.

python_plugin(…) : Create a plugin operator from the python class.

range(…) : Return a tensor of evenly spaced values within a interval.

repeat(…) : Repeat the elements along the given axis.

reset_workspace(…) : Reset the current default workspace.

reshape(…) : Change the dimensions of input.

reverse(…) : Reverse elements along the given axis.

roll(…) : Roll elements along the given axis.

scatter_add(…) : Add elements along the given axis of index.

scatter_elements(…) : Update elements along the given axis of index.

set_num_threads(…) : Set the number of threads for cpu parallelism.

shape(…) : Return the shape of input.

slice(…) : Select the elements according to the given sections.

sort(…) : Return the sorted elements along the given axis.

split(…) : Split the input into chunks along the given axis.

squeeze(…) : Remove the dimensions of input with size 1.

stack(…) : Stack the inputs along the given axis.

stop_gradient(…) : Return the identity of input with truncated gradient-flow.

tile(…) : Repeat elements along each axis of input.

transpose(…) : Permute the dimensions of input.

tril(…) : Return the lower triangular part of input.

triu(…) : Return the upper triangular part of input.

unique(…) : Return the unique elements of input.

where(…) : Select the elements from two branches under the condition.

zeros(…) : Return a tensor filled with zeros.

zeros_like(…) : Return a tensor of zeros with shape as the other.