vm.tensorflow¶
Classes¶
class GradientTape : Record the operations for auto differentiation.
class Module : The base class of neural network modules.
class TensorShape : Represent the a sequence of dimensions.
class TensorSpec : Spec to describe properties of a tensor.
Functions¶
argsort(…) : Return the index of sorted elements along the given axis.
broadcast_to(…) : Broadcast input according to a given shape.
cast(…) : Cast the data type of input.
clip_by_value(…) : Compute the clipped input according to the given bounds.
concat(…) : Concatenate the values along the given axis.
constant(…) : Return a tensor initialized from the value.
convert_to_tensor(…) : Convert the given value to a tensor.
device(…) : Context-manager to nest the device spec.
expand_dims(…) : Expand the dimensions of input with size 1.
eye(…) : Return a tensor constructed as the identity matrix.
fill(…) : Return a tensor filled with the scalar value.
gather(…) : Gather the elements along the given axis using index.
function(…) : Create a callable graph from the python function.
identity(…) : Return a tensor copied from the input.
linspace(…) : Generate evenly spaced values within intervals along the given axis.
name_scope(…) : Context-manager to nest the name as prefix for operations.
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.
range(…) : Return a tensor of evenly spaced values within a interval.
reshape(…) : Change the dimensions of input.
reverse(…) : Reverse elements along the given axis.
roll(…) : Roll elements along the given axis.
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 input into chunks along the given axis.
squeeze(…) : Remove the dimensions of input with size 1.
tile(…) : Tile input according to the given repeats.
transpose(…) : Permute the dimensions of input.
unique(…) : Return the unique elements of input.
unique_with_counts(…) : Return the unique elements of input with counts.
unstack(…) : Unpack input into chunks along the given axis.
zeros(…) : Return a tensor filled with zeros.
zeros_like(…) : Return a tensor of zeros with shape as the other.