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.
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 of 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.
unstack(…) : Unpack input into chunks along the given axis.
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.