TIM-VX/src/tim/vx/ops

INFO: Actual implementations may differ from reference link in terms of dimensions and parameters supported

TIM-VX API	Internal Op	Status	Reference
Add	ADD	Mapped	tf.math.add
Multiply	MULTIPLY	Mapped	tf.math.multiply
Conv2d	CONV2D	Mapped	tf.nn.conv2d tf.nn.atros_conv2d tf.nn.depthwise_conv2d
Conv3d	CONV3D	Mapped	tf.nn.conv3d
Softmax	SOFTMAX	Mapped	tf.nn.softmax
Pool2d	POOL	Mapped	tf.nn.pool
Pool1d	POOL	Mapped	tf.nn.pool
LeakyRelu	LEAKY_RELU	Mapped	tf.nn.leaky_relu
Concat	CONCAT	Mapped	tf.concat
Split	SPLIT	Mapped	tf.split
BatchNorm	BATCH_NORM	Mapped	tf.nn.batch_normalization
DeConv2d	DECONVOLUTION	Mapped	tf.nn.conv2d_transpose
Reshape	RESHAPE	Mapped	tf.reshape
Transpose	PERMUTE	Mapped	tf.transpose
Prelu	PRELU	Mapped	tf.keras.layers.PReLU
MaxUnpool2d	UPSAMPLE	Mapped	tfa.layers.MaxUnpooling2D
Relu	RELU	Mapped	tf.nn.relu
Reorg	REORG	Mapped	darknet.reorg
L2Normalization	L2_NORMALIZE	Mapped	tf.math.l2_normalize
FullyConnected	FCL2	Mapped	tf.keras.layers.Dense
Dense	FCL	Mapped	tf.keras.layers.Dense
MaxpoolWithArgmax	POOLWITHARGMAX	Mapped	tf.nn.max_pool_with_argmax
MaxpoolWithArgmax2	MAXPOOLWITHARGMAX	Mapped	tf.nn.max_pool_with_argmax
ArgMax	ARGMAX	Mapped	tf.math.argmax
Maximum	MAXIMUM	Mapped	tf.math.maximum
Sub	SUBTRACT	Mapped	tf.math.subtract
Relu6	RELU6	Mapped	tf.nn.relu6
Sigmoid	SIGMOID	Mapped	tf.math.sigmoid
Tanh	TANH	Mapped	tf.math.tanh
Sqrt	SQRT	Mapped	tf.math.sqrt
Rsqrt	RSQRT	Mapped	tf.math.rsqrt
SoftRelu	SOFTRELU	Mapped	tf.math.softplus
Div	DIVIDE	Mapped	tf.math.divide
Dropout	DROPOUT	Mapped	f(x) = x*ratio
Resize	RESIZE	Mapped	tf.image.resize
Reverse	REVERSE	Mapped	tf.reverse
DepthToSpace	DEPTH2SPACE	Mapped	tf.nn.depth_to_space
SpaceToDepth	SPACE2DEPTH	Mapped	tf.nn.space_to_depth
DataConvert	DATACONVERT	Mapped	Data Format Conversion
Slice	SLICE	Mapped	tf.slice
Elu	ELU	Mapped	tf.nn.elu
Batch2Space	BATCH2SPACE	Mapped	tf.batch_to_space
Space2Batch	SPACE2BATCH	Mapped	tf.space_to_batch
Pad	PAD	Mapped	tf.pad
Matmul	MATRIXMUL	Mapped	tf.linalg.matmul
PadV2	PAD2	Mapped	tf.raw_ops.PadV2
Matmul	MATRIXMUL	Mapped	tf.linalg.matmul
LayerNormalization	LAYER_NORM	Mapped	tf.keras.layers.LayerNormalization
ReduceMin	REDUCE_MIN	Mapped	tf.math.reduce_min
ReduceMax	REDUCE_MAX	Mapped	tf.math.reduce_max
ReduceAny	REDUCE_ANY	Mapped	tf.math.reduce_any
ReduceProd	REDUCE_PROD	Mapped	tf.math.reduce_prod
ReduceMean	REDUCE_MEAN	Mapped	tf.math.reduce_mean
ReduceAll	REDUCE_ALL	Mapped	tf.math.reduce_all
ReduceSum	REDUCE_SUM	Mapped	tf.math.reduce_sum
InstanceNormalization	INSTANCE_NORM	Mapped	tfa.layers.InstanceNormalization
StridedSlice	STRIDED_SLICE	Mapped	tf.strided_slice
Abs	ABS	Mapped	tf.math.abs
Conv1d	CONV1D	Mapped	tf.nn.conv1d
NBG	NBG	Mapped	Network Binary Graph
LocalResponseNormalization	LRN2	Mapped	tf.nn.local_response_normalization
Greater	RELATIONAL_OPS_GREATER	Mapped	tf.math.greater
GreaterOrEqual	RELATIONAL_OPS_GREATER_EQUAL	Mapped	tf.math.greater_equal
Less	RELATIONAL_OPS_LESS	Mapped	tf.math.less
LessOrEqual	RELATIONAL_OPS_LESS_EQUAL	Mapped	tf.math.less_equal
Equal	RELATIONAL_OPS_EQUAL	Mapped	tf.math.equal
NotEqual	RELATIONAL_OPS_NOT_EQUAL	Mapped	tf.math.not_equal
Pow	POW	Mapped	tf.math.pow
FloorDiv	FLOORDIV	Mapped	tf.math.floordiv
Minimum	MINIMUM	Mapped	tf.math.minimum
And	LOGICAL_OPS	Mapped	tf.math.logical_and
Or	LOGICAL_OPS	Mapped	tf.math.logical_or
Select	SELECT	Mapped	tf.where
Relu1	RELU1	Mapped	tf.keras.layers.ReLU(max_value=1.0)
Stack	STACK	Mapped	tf.stack
Floor	FLOOR	Mapped	tf.math.floor
Square	SQUARE	Mapped	tf.math.square
Neg	NEG	Mapped	tf.math.negative
Exp	EXP	Mapped	tf.math.exp
Clip	CLIP	Mapped	tf.clip_by_value
AddN	ADDN	Mapped	tf.math.add_n
Gather	GATHER	Mapped	tf.gather
Gather_elements	GATHER_ELEMENTS	Mapped	onnx/GatherElements
LogicalNot	LOGICAL_NOT	Mapped	tf.math.logical_not
Sin	SIN	Mapped	tf.math.sin
Log	LOG	Mapped	tf.math.log
ArgMin	ARGMIN	Mapped	tf.math.argmin
LogSoftmax	LOG_SOFTMAX	Mapped	tf.nn.log_softmax
Swish	SWISH	Mapped	tf.keras.activations.swish
HardSwish	SWISH	Mapped	torch.nn.Hardswish
GatherNd	GATHER_ND	Mapped	tf.gather_nd
Cast	CAST	Mapped	tf.cast
Moments	MOMENTS	Mapped	tf.moments
Squeeze	SQUEEZE	Mapped	tf.squeeze
HardSigmoid	HARD_SIGMOID	Mapped	tf.keras.activations.hard_sigmoid
Mish	MISH	Mapped	tfa.activations.mish
DeConv1d	DECONVOLUTION1D	Mapped	tf.nn.conv1d_transpose
Resize1d	RESIZE_1D	Mapped	Onnx.resize 1D image
Linear	LINEAR	Mapped	tf.keras.activations.linear
ScatterND	SCATTER_ND	Mapped	tf.scatter_nd
Unstack	UNSTACK	Mapped	tf.unstack
Tile	TILE	Mapped	tf.tile
GroupedConv2d	GROUPED_CONV2D	Mapped	ANEURALNETWORKS_GROUPED_CONV_2D
SpatialTransformer	SPATIAL_TRANSFORMER	Mapped	SpatialTransformer
ShuffleChannel	SHUFFLECHANNEL	Mapped	ANEURALNETWORKS_CHANNEL_SHUFFLE
Gelu	GELU	Mapped	tf.nn.gelu
Svdf	SVDF	Mapped	ANEURALNETWORKS_SVDF
Erf	ERF	Mapped	tf.math.erf
GroupedConv1d	GROUPED_CONV1D	Mapped	tf.keras.layers.Conv1D
SignalFrame	SIGNAL_FRAME	Mapped	tf.signal.frame
RNNCell	RNNCELL_OVXLIB	Mapped	ANEURALNETWORKS_RNN
BroadCast	EXPAND_BROADCAST	Mapped	numpy.broadcast_to
RoiPool	ROI_POOL	Mapped	ANEURALNETWORKS_ROI_POOLING
ROI_Align	ROI_ALIGN	Mapped	ANEURALNETWORKS_ROI_ALIGN
Topk	TOPK	Mapped (limited support)	tf.math.top_k
GRUCell	GRUCELL_OVXLIB	Mapped	tf.keras.layers.GRUCell
UnidirectionalSequenceGRU	GRU_OVXLIB	Mapped	tf.keras.layers.GRU
Mod	MOD	Mapped	Onnx.Mod
Selu	SELU	Mapped	tf.keras.activations.selu
Celu	CELU	Mapped	Onnx.celu
Sign	SIGN	Mapped	tf.math.sign
SoftSign	SOFTSIGN	Mapped	tf.keras.activations.softsign
CumSum	CUMSUM	Mapped	tf.math.cumsum
Rcp	RCP	Mapped	tf.math.reciprocal
MaxPool3d	MAX_POOL3D	Mapped	Onnx.MaxPool
UnidirectionalSequenceRNN	UNIDIRECTIONAL_SEQUENCE_RNN	Mapped	ANEURALNETWORKS_UNIDIRECTIONAL_SEQUENCE_RNN
BidirectionalSequenceRNN	BIDIRECTIONAL_SEQUENCE_RNN	Mapped	ANEURALNETWORKS_BIDIRECTIONAL_SEQUENCE_RNN
BidirectionalSequenceLSTM	LSTM_OVXLIB	Composed in tim-vx	ANEURALNETWORKS_BIDIRECTIONAL_SEQUENCE_LSTM
UnidirectionalSequenceLSTM	LSTM_OVXLIB	Mapped	ANEURALNETWORKS_UNIDIRECTIONAL_SEQUENCE_LSTM
LSTMCell	LSTMUNIT_OVXLIB	replace with UnidirectionalSequenceLSTM by set n_step = 1	ANEURALNETWORKS_LSTM
HashtableLookup	HASHTABLE_LOOKUP	Mapped	ANEURALNETWORKS_HASHTABLE_LOOKUP
EmbeddingLookup	EMBEDDING_LOOKUP	Mapped	ANEURALNETWORKS_EMBEDDING_LOOKUP
Round	ROUND	Mapped	tf.math.round
Ceil	CEIL	Mapped	tf.math.ceil
OneHot	ONE_HOT	Mapped	tf.one_hot
	PRE_PROCESS	TBD	Image Preprocessing (YUV2RGB, Input Normalization, Resizing, etc)
	PROPOSAL	TBD	Faster-RCNN Proposal Layer
	HEATMAP_MAX_KEYPOINT	TBD	ANEURALNETWORKS_HEATMAP_MAX_KEYPOINT
	AXIS_ALIGNED_BBOX_TRANSFORM	TBD	ANEURALNETWORKS_AXIS_ALIGNED_BBOX_TRANSFORM
	BOX_WITH_NMS_LIMIT	TBD	ANEURALNETWORKS_BOX_WITH_NMX_LIMIT
	GENERATE_PROPOSALS	TBD	ANEURALNETWORKS_GENERATE_PROPOSALS
	DETECTION_POSTPROCESS	TBD	ANEURALNETWORKS_DETECTION_POSTPROCESSING
	RANDOM_MULTINOMIAL	TBD	ANEURALNETWORKS_RANDOM_MULTINOMIAL](https://developer.android.com/ndk/reference/group/neural-networks#group___neural_networks_1ggaabbe492c60331b13038e39d4207940e0a6cb5032c09d3c4b542d18495c247b5b4)
	UPSAMPLESCALE	TBD	Unoffical Caffe layer
	GROUP_NORM	TBD	tf.layers.GroupNormalization](https://tensorflow.google.cn/addons/api_docs/python/tfa/layers/GroupNormalization)
	SEQUENCE_MASK	TBD	tf.math.ceil
	REPEAT	TBD	tf.repeat
	NMS	TBD	tf.image.non_max_suppression
	SCATTER_ND_UPDATE	TBD	tf.compat.v1.scatter_nd_update
	LSH_PROJECTION	Deprecated
	CONV_RELU	Deprecated
	CONV_RELU_POOL	Deprecated
	FCL	Deprecated
	FCL_RELU	Deprecated
	LRN	Deprecated
	SCALE	Deprecated
	DEPTHWISE_CONV1D	Deprecated
	L2NORMALIZESCALE	Deprecated
	INTERP	Deprecated
	NOOP	Deprecated
	TENSORSTACKCONCAT	Deprecated
	VARIABLE	InternalOnly
	RELUN	Deprecated
	CROP	Deprecated
	TENSOR_ADD_MEAN_STDDEV_NORM	InternalOnly
	RNN	Deprecated
	LSTMUNIT_ACTIVATION	InternalOnly
	LSTM	Deprecated
	LSTMUNIT	Deprecated
	QUANTIZED_16BIT_LSTM	InternalOnly
	RELU_KERAS	Deprecated
	PRE_PROCESS_GRAY	InternalOnly
	PRE_PROCESS_YUV444	InternalOnly
	PRE_PROCESS_NV12	InternalOnly
	PRE_PROCESS_YUV420	InternalOnly
	PRE_PROCESS_BGRA	InternalOnly
	PRE_PROCESS_TENSOR	InternalOnly
	IMAGEPROCESS	Deprecated
	POST_PROCESS	InternalOnly
	EXTRA_ENDING	InternalOnly
	SYNC_HOST	InternalOnly
	BATCHNORM_SINGLE	InternalOnly
	CONCATSHIFT	InternalOnly
	A_TIMES_B_PLUS_C	Deprecated	tf.add(tf.mul(A, B), C)