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Python v0.3.0
dragon
DeviceSpec
GradientTape
Tensor
Workspace
argsort
assign
boolean_mask
broadcast_to
cast
concat
constant
device
eager_mode
expand_dims
eye
eye_like
fill
flatten
function
gather
gather_elements
get_num_threads
get_workspace
graph_mode
identity
linspace
load_library
name_scope
nonzero
ones
ones_like
one_hot
pad
python_plugin
range
repeat
reset_workspace
reshape
reverse
roll
scatter_add
scatter_elements
set_num_threads
shape
slice
sort
split
squeeze
stack
stop_gradient
tile
transpose
tril
triu
unique
unstack
variable_scope
where
zeros
zeros_like
dragon.autograph
set_optimization
set_scheduler
set_verbosity
dragon.bitwise
bitwise_and
bitwise_or
bitwise_xor
invert
dragon.cuda
Stream
current_device
get_device_capability
get_device_name
is_available
memory_allocated
set_cublas_flags
set_cudnn_flags
set_default_device
set_device
synchronize
dragon.distributed
all_reduce
broadcast
is_initialized
is_mpi_available
is_nccl_available
get_backend
get_group
get_rank
get_world_size
new_group
dragon.dlpack
from_dlpack
to_dlpack
dragon.logging
debug
error
fatal
get_verbosity
info
log
set_directory
set_verbosity
warning
dragon.losses
ctc_loss
l1_loss
l2_loss
nll_loss
sigmoid_cross_entropy_loss
sigmoid_focal_loss
smooth_l1_loss
softmax_cross_entropy_loss
dragon.math
abs
add
affine
argmax
argmin
atan2
ceil
clip
cos
cumsum
div
equal
exp
floor
gemm
greater
greater_equal
is_finite
is_inf
is_nan
less
less_equal
log
logical_and
logical_not
logical_or
logical_xor
matmul
max
maximum
mean
min
minimum
mul
negative
norm
not_equal
pow
reciprocal
round
rsqrt
sigmoid
sign
sin
sqrt
square
sub
sum
tanh
top_k
var
dragon.metrics
accuracy
dragon.mps
current_device
get_device_family
is_available
set_default_device
set_device
synchronize
dragon.nn
GRU
LSTM
RNN
batch_norm
bias_add
channel_norm
channel_shuffle
conv
conv_transpose
conv1d
conv1d_transpose
conv2d
conv2d_transpose
conv3d
conv3d_transpose
depthwise_conv2d
depth_to_space
dropout
drop_block
drop_path
elu
gelu
group_norm
hardsigmoid
hardswish
instance_norm
layer_norm
leaky_relu
local_response_norm
log_softmax
lp_norm
moments
pool
pool1d
pool2d
pool3d
prelu
relu
relu6
selu
silu
softmax
space_to_depth
sync_batch_norm
dragon.onnx
BackendRep
prepare_backend
export
record
run_model
supports_device
dragon.optimizers
Adam
AdamW
Optimizer
RMSprop
SGD
dragon.random
glorot_normal
glorot_uniform
multinomial
normal
normal_like
permutation
set_seed
truncated_normal
uniform
uniform_like
dragon.sysconfig
get_build_info
get_include
get_lib
dragon.vision
extract_patches
resize
roi_align
roi_pool
vm.dali
Iterator
Pipeline
device
get_device_type
get_distributed_info
vm.dali.ops
BbFlip
BBoxPaste
Brightness
BrightnessContrast
Cast
CoinFlip
ColorSpaceConversion
ColorTwist
Contrast
CropMirrorNormalize
Erase
ExternalSource
GaussianBlur
Hsv
ImageDecoder
ImageDecoderRandomCrop
Normalize
Pad
Paste
RandomBBoxCrop
RandomResizedCrop
Reshape
Resize
Rotate
Slice
TFRecordReader
Uniform
WarpAffine
vm.tensorflow
GradientTape
Module
TensorShape
TensorSpec
argsort
broadcast_to
cast
clip_by_value
concat
constant
convert_to_tensor
device
expand_dims
eye
fill
function
gather
identity
linspace
name_scope
ones
ones_like
one_hot
pad
range
reshape
reverse
roll
shape
slice
sort
split
squeeze
tile
transpose
unique
unique_with_counts
unstack
zeros
zeros_like
vm.tensorflow.bitwise
bitwise_and
bitwise_or
bitwise_xor
invert
vm.tensorflow.dtypes
DType
as_dtype
vm.tensorflow.keras
Input
Sequential
activations
elu
exponential
get
hard_sigmoid
linear
relu
selu
sigmoid
softmax
swish
tanh
initializers
Constant
GlorotNormal
GlorotUniform
Initializer
Ones
RandomNormal
RandomUniform
TruncatedNormal
VarianceScaling
Zeros
get
layers
Activation
Add
AveragePooling1D
AveragePooling2D
AveragePooling3D
BatchNormalization
Concatenate
Conv1D
Conv1DTranspose
Conv2D
Conv2DTranspose
Conv3D
Conv3DTranspose
Dense
DepthwiseConv2D
Dropout
ELU
Flatten
GlobalAveragePooling1D
GlobalAveragePooling2D
GlobalAveragePooling3D
GlobalMaxPool1D
GlobalMaxPool2D
GlobalMaxPool3D
Layer
LayerNormalization
LeakyReLU
Maximum
MaxPool1D
MaxPool2D
MaxPool3D
Minimum
Multiply
Permute
ReLU
Reshape
SELU
Softmax
Subtract
UpSampling1D
UpSampling2D
UpSampling3D
ZeroPadding1D
ZeroPadding2D
ZeroPadding3D
losses
BinaryCrossentropy
CategoricalCrossentropy
Loss
MeanAbsoluteError
MeanSquaredError
SparseCategoricalCrossentropy
binary_crossentropy
categorical_crossentropy
get
mean_absolute_error
mean_squared_error
sparse_categorical_crossentropy
optimizers
Adam
Optimizer
RMSprop
SGD
regularizers
L1
L1L2
L2
Regularizer
get
l1_l2
vm.tensorflow.linalg
matmul
vm.tensorflow.math
abs
add
add_n
argmax
argmin
atan2
ceil
cos
cumsum
divide
equal
exp
floor
greater
greater_equal
is_finite
is_inf
is_nan
l2_normalize
less
less_equal
log
multiply
negative
not_equal
pow
reciprocal
reduce_max
reduce_mean
reduce_min
reduce_sum
reduce_variance
round
rsqrt
sigmoid
sign
sin
sqrt
square
subtract
tanh
top_k
vm.tensorflow.nn
avg_pool
avg_pool1d
avg_pool2d
avg_pool3d
bias_add
conv1d
conv1d_transpose
conv2d
conv2d_transpose
conv3d
conv3d_transpose
convolution
conv_transpose
depthwise_conv2d
depth_to_space
dropout
elu
fused_batch_norm
gelu
l2_loss
leaky_relu
local_response_normalization
log_softmax
max_pool
max_pool1d
max_pool2d
max_pool3d
moments
relu
relu6
selu
sigmoid_cross_entropy_with_logits
silu
softmax
softmax_cross_entropy_with_logits
space_to_depth
sparse_softmax_cross_entropy_with_logits
vm.tensorflow.random
normal
truncated_normal
uniform
vm.tensorrt
Binding
Engine
vm.tensorrt.onnx
BackendRep
prepare_backend
run_model
run_node
supports_device
vm.torch
Size
Tensor
abs
add
addmm
arange
argmax
argmin
argsort
atan2
baddbmm
bitwise_and
bitwise_not
bitwise_or
bitwise_xor
bmm
cat
ceil
chunk
clamp
cos
cumsum
device
div
dtype
empty
enable_grad
eq
exp
eye
flatten
flip
fliplr
flipud
floor
from_numpy
full
full_like
gather
ge
gt
index_select
isfinite
isinf
isnan
le
linspace
log
logical_and
logical_not
logical_or
logical_xor
logsumexp
lt
masked_select
matmul
max
maximum
mean
min
minimum
mm
mul
multinomial
narrow
ne
neg
no_grad
nonzero
norm
ones
ones_like
permute
pow
rand
randn
randperm
reciprocal
reshape
roll
round
rsqrt
scatter
scatter_add
set_grad_enabled
sign
sin
sort
split
sqrt
square
squeeze
stack
sub
sum
tensor
tile
topk
transpose
tril
triu
unbind
unique
unsqueeze
where
var
var_mean
zeros_like
zeros
vm.torch.autograd
backward
vm.torch.backends
cuda
cudnn
mps
openmp
vm.torch.cuda
current_device
get_device_capability
get_device_name
is_available
set_device
synchronize
vm.torch.distributed
all_reduce
broadcast
vm.torch.jit
trace
vm.torch.nn
AdaptiveAvgPool1d
AdaptiveAvgPool2d
AdaptiveAvgPool3d
AdaptiveMaxPool1d
AdaptiveMaxPool2d
AdaptiveMaxPool3d
Affine
AvgPool1d
AvgPool2d
AvgPool3d
BatchNorm1d
BatchNorm2d
BatchNorm3d
BCEWithLogitsLoss
ChannelShuffle
ConstantPad1d
ConstantPad2d
ConstantPad3d
Conv1d
Conv2d
Conv3d
ConvTranspose1d
ConvTranspose2d
ConvTranspose3d
CosineSimilarity
CrossEntropyLoss
CTCLoss
DepthwiseConv2d
DropBlock2d
Dropout
DropPath
ELU
Flatten
GELU
GroupNorm
GRU
GumbelSoftmax
Hardsigmoid
Hardswish
Identity
KLDivLoss
L1Loss
LayerNorm
LeakyReLU
Linear
LocalResponseNorm
LogSoftmax
LSTM
LSTMCell
MaxPool1d
MaxPool2d
MaxPool3d
Module
ModuleList
MSELoss
MultiheadAttention
NLLLoss
Parameter
PixelShuffle
PixelUnshuffle
PReLU
ReflectionPad1d
ReflectionPad2d
ReflectionPad3d
ReLU
ReLU6
ReplicationPad1d
ReplicationPad2d
ReplicationPad3d
RNN
SELU
Sequential
Sigmoid
SigmoidFocalLoss
SiLU
SmoothL1Loss
Softmax
Tanh
TransformerDecoder
TransformerDecoderLayer
TransformerEncoder
TransformerEncoderLayer
SyncBatchNorm
Unfold
Upsample
UpsamplingBilinear2d
UpsamplingNearest2d
ZeroPad2d
vm.torch.nn.functional
adaptive_avg_pool1d
adaptive_avg_pool2d
adaptive_avg_pool3d
adaptive_max_pool1d
adaptive_max_pool2d
adaptive_max_pool3d
affine
avg_pool1d
avg_pool2d
avg_pool3d
batch_norm
binary_cross_entropy_with_logits
channel_norm
channel_shuffle
conv1d
conv2d
conv3d
conv_transpose1d
conv_transpose2d
conv_transpose3d
cosine_similarity
cross_entropy
ctc_loss
depthwise_conv2d
drop_block2d
drop_path
dropout
elu
gelu
group_norm
hardsigmoid
hardswish
kl_div
l1_loss
leaky_relu
linear
layer_norm
local_response_norm
log_softmax
interpolate
max_pool1d
max_pool2d
max_pool3d
mse_loss
multi_head_attention_forward
nll_loss
normalize
one_hot
pad
pixel_shuffle
pixel_unshuffle
prelu
relu
relu6
selu
sigmoid
sigmoid_focal_loss
silu
smooth_l1_loss
softmax
sync_batch_norm
tanh
unfold
upsample
upsample_bilinear
upsample_nearest
vm.torch.nn.init
calculate_gain
constant_
dirac_
eye_
xavier_normal_
kaiming_uniform_
normal_
ones_
trunc_normal_
uniform_
kaiming_normal_
xavier_uniform_
zeros_
vm.torch.onnx
export
vm.torch.optim
Adam
AdamW
LARS
Optimizer
RMSprop
SGD
vm.torch.utils.checkpoint
checkpoint
checkpoint_sequential
no_checkpoint
vm.torch.utils.dlpack
from_dlpack
to_dlpack
vm.torchvision.ops
roi_align
roi_pool
Dragon
API
Dragon v0.3.0
Python
dragon.metrics
¶
Functions
¶
accuracy(…)
: Compute the top-k accuracy.
dragon.metrics
Functions