15 KiB
15 KiB
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 |
| Softmax | SOFTMAX | Mapped | tf.nn.softmax |
| Pool2d | POOL | Mapped | tf.nn.pool |
| LeakyRelu | LEAKY_RELU | Mapped | tf.nn.leaky_relu |
| Concat | CONCAT | Mapped | tf.concat |
| Split | SPLIT | Mapped | tf.split |
| NOOP | Unmapped | ||
| ROI_POOL | Unmapped | ANEURALNETWORKS_ROI_POOLING | |
| BatchNorm | BATCH_NORM | Mapped | tf.nn.batch_normalization |
| PROPOSAL | Unmapped | ||
| 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 | Recover pixel from the outputs of MaxpoolWithArgmax. |
| Relu | RELU | Mapped | tf.nn.relu |
| RELUN | Deprecated | tf.keras.layers.ReLU(max_value=N) | |
| Reorg | REORG | Mapped | darknet.reorg |
| VARIABLE | Unmapped | tf.variable | |
| L2Normalization | L2_NORMALIZE | Mapped | tf.math.l2_normalize |
| FullyConnected | FCL2 | Mapped | tf.keras.layers.Dense |
| MaxpoolWithArgmax | POOLWITHARGMAX | Mapped | tf.nn.max_pool_with_argmax |
| ArgMax | ARGMAX | Mapped | tf.math.argmax |
| Maximum | MAXIMUM | Mapped | tf.math.maximum |
| CROP | Unmapped | ||
| 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 |
| SHUFFLECHANNEL | Unmapped | ANEURALNETWORKS_CHANNEL_SHUFFLE | |
| 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 | |
| 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 |
| MATRIXMUL | Unmapped | tf.experimental.numpy.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 |
| InstanceNormalization | INSTANCE_NORM | Mapped | tfa.layers.InstanceNormalization |
| TENSORSTACKCONCAT | Unmapped | ||
| StridedSlice | STRIDED_SLICE | Mapped | tf.strided_slice |
| SIGNAL_FRAME | Unmapped | ||
| A_TIMES_B_PLUS_C | Unmapped | tf.add(tf.mul(A, B), C) | |
| SVDF | Unmapped | ANEURALNETWORKS_SVDF | |
| Abs | ABS | Mapped | tf.math.abs |
| Conv1d | CONV1D | Mapped | tf.nn.conv1d |
| NBG | NBG | Mapped | |
| CONCATSHIFT | Unmapped | ||
| 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 |
| SPATIAL_TRANSFORMER | Unmapped | ||
| And | LOGICAL_OPS | Mapped | tf.math.logical_and |
| Or | LOGICAL_OPS | Mapped | tf.math.logical_or |
| Select | SELECT | Mapped | tf.where |
| TENSOR_ADD_MEAN_STDDEV_NORM | Unmapped | ||
| 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 |
| HASHTABLE_LOOKUP | Unmapped | ANEURALNETWORKS_HASHTABLE_LOOKUP | |
| EMBEDDING_LOOKUP | Unmapped | ANEURALNETWORKS_EMBEDDING_LOOKUP | |
| LSH_PROJECTION | Unmapped | ANEURALNETWORKS_LSH_PROJECTION | |
| RNN | Unmapped | ANUERALNETWORKS_RNN | |
| Clip | CLIP | Mapped | tf.clip_by_value |
| UNSTACK | Unmapped | tf.unstack | |
| PRE_PROCESS | Unmapped | ||
| PRE_PROCESS_RGB | Unmapped | ||
| PRE_PROCESS_GRAY | Unmapped | ||
| PRE_PROCESS_YUV444 | Unmapped | ||
| PRE_PROCESS_NV12 | Unmapped | ||
| PRE_PROCESS_YUV420 | Unmapped | ||
| PRE_PROCESS_BGRA | Unmapped | ||
| PRE_PROCESS_TENSOR | Unmapped | ||
| IMAGEPROCESS | Unmapped | ||
| POST_PROCESS | Unmapped | ||
| AddN | ADDN | Mapped | tf.math.add_n |
| Gather | GATHER | Mapped | tf.gather |
| TILE | Unmapped | tf.tile | |
| GROUPED_CONV2D | Unmapped | ANEURALNETWORKS_GROUPED_CONV_2D | |
| TOPK | Unmapped | tf.math.top_k | |
| 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 |
| ROI_ALIGN | Unmapped | ANEURALNETWORKS_ROI_ALIGN | |
| HEATMAP_MAX_KEYPOINT | Unmapped | ANEURALNETWORKS_HEATMAP_MAX_KEYPOINT | |
| AXIS_ALIGNED_BBOX_TRANSFORM | Unmapped | ANEURALNETWORKS_AXIS_ALIGNED_BBOX_TRANSFORM | |
| BOX_WITH_NMS_LIMIT | Unmapped | ANEURALNETWORKS_BOX_WITH_NMX_LIMIT | |
| GENERATE_PROPOSALS | Unmapped | ANEURALNETWORKS_GENERATE_PROPOSALS | |
| DETECTION_POSTPROCESS | Unmapped | ANEURALNETWORKS_DETECTION_POSTPROCESSING | |
| RANDOM_MULTINOMIAL | Unmapped | ANEURALNETWORKS_RANDOM_MULTINOMIAL | |
| LogSoftmax | LOG_SOFTMAX | Mapped | tf.nn.log_softmax |
| RELU_KERAS | Unmapped | tf.keras.layers.ReLU | |
| GRU_OVXLIB | Unmapped | ||
| GRUCELL_OVXLIB | Unmapped | ||
| UNIDIRECTIONAL_SEQUENCE_RNN | Unmapped | ||
| QUANTIZED_16BIT_LSTM | Unmapped | ||
| BIDIRECTIONAL_SEQUENCE_RNN | Unmapped | ||
| BIDIRECTIONAL_SEQUENCE_LSTM | Unmapped | ||
| RNNCELL_OVXLIB | Unmapped | ||
| LSTM | Unmapped | tf.keras.layers.LSTM | |
| LSTM_OVXLIB | Unmapped | ||
| LSTMUNIT | Unmapped | ||
| LSTMUNIT_ACTIVATION | Unmapped | ||
| LSTMUNIT_OVXLIB | Unmapped | ||
| HardSwish | SWISH | Mapped | tf.keras.activations.swish |
| GatherNd | GATHER_ND | Mapped | tf.gather_nd |
| Cast | CAST | Mapped | tf.cast |
| LINEAR | Unmapped | f(x) = a*x + b | |
| BATCHNORM_SINGLE | Unmapped | tf.nn.batch_normalization | |
| MOMENTS | Unmapped | tf.moments | |
| Squeeze | SQUEEZE | Mapped | tf.squeeze |
| HardSigmoid | HARD_SIGMOID | Mapped | tf.keras.activations.hard_sigmoid |
| Mish | MISH | Mapped | tfa.activations.mish |
| EXPAND_BROADCAST | Unmapped | ||
| SCATTER_ND | Unmapped | tf.scatter_nd | |
| DeConv1d | DECONVOLUTION1D | Mapped | tf.nn.conv1d_transpose |
| Resize1d | RESIZE_1D | Mapped | Onnx.resize 1D image |
| CONV_RELU | Deprecated | ||
| CONV_RELU_POOL | Deprecated | ||
| FCL | Deprecated | ||
| FCL_RELU | Deprecated | ||
| LRN | Deprecated | ||
| SCALE | Deprecated | ||
| DEPTHWISE_CONV1D | Deprecated | ||
| L2NORMALIZESCALE | Deprecated | ||
| INTERP | Deprecated | ||
| EXTRA_ENDING | InternalOnly | ||
| SYNC_HOST | InternalOnly |