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Supported OPs - TensorFlow

The TensorFlow operations supported by the RBLN SDK are listed in the table below. This list will continue to expand with subsequent updates to the RBLN SDK.

TF Ops Supported Accelerated Note
tf.abs O O -
tf.acos O - -
tf.acosh O - -
tf.add O O -
tf.add_n O O -
tf.argmin O - -
tf.argsort O - -
tf.asin O - -
tf.asinh O - -
tf.atan O - -
tf.atanh O - -
tf.boolean_mask O - -
tf.broadcast_to O O -
tf.cast O O -
tf.clip_by_norm O - -
tf.clip_by_value O O -
tf.concat O O -
tf.constant O O -
tf.cos O - -
tf.cosh O - -
tf.divide O O -
tf.dtypes.cast O O -
tf.einsum O - -
tf.equal O - -
tf.exp O O -
tf.expand_dims O O -
tf.floor O O -
tf.gather_nd O - -
tf.greater O - -
tf.greater_equal O - -
tf.histogram_fixed_width_bins O - -
tf.identity O O -
tf.keras.activations.exponential O O -
tf.keras.activations.gelu O O -
tf.keras.activations.hard_sigmoid O O -
tf.keras.activations.linear O O -
tf.keras.activations.relu O O -
tf.keras.activations.sigmoid O O -
tf.keras.activations.softplus O O -
tf.keras.activations.softsign O O -
tf.keras.activations.swish O O -
tf.keras.activations.tanh O O -
tf.keras.layers.AdditiveAttention O O -
tf.keras.layers.Attention O O -
tf.keras.layers.AveragePooling1D O O -
tf.keras.layers.AveragePooling2D O O -
tf.keras.layers.AveragePooling3D O O -
tf.keras.layers.AvgPool1D O O -
tf.keras.layers.AvgPool2D O O -
tf.keras.layers.AvgPool3D O O -
tf.keras.layers.BatchNormalization O O -
tf.keras.layers.Conv1D O O -
tf.keras.layers.Conv1DTranspose O O -
tf.keras.layers.Conv2D O O -
tf.keras.layers.Conv2DTranspose O O -
tf.keras.layers.Conv3D O O -
tf.keras.layers.Conv3DTranspose O O -
tf.keras.layers.Convolution1D O O -
tf.keras.layers.Convolution1DTranspose O O -
tf.keras.layers.Convolution2D O O -
tf.keras.layers.Convolution2DTranspose O O -
tf.keras.layers.Convolution3D O O -
tf.keras.layers.Convolution3DTranspose O O -
tf.keras.layers.Cropping1D O O -
tf.keras.layers.Cropping2D O O -
tf.keras.layers.Cropping3D O O -
tf.keras.layers.Dense O O -
tf.keras.layers.DepthwiseConv2D O O -
tf.keras.layers.ELU O O -
tf.keras.layers.Embedding O - -
tf.keras.layers.Flatten O O -
tf.keras.layers.GlobalAveragePooling1D O O -
tf.keras.layers.GlobalAveragePooling2D O O -
tf.keras.layers.GlobalAveragePooling3D O O -
tf.keras.layers.GlobalAvgPool1D O O -
tf.keras.layers.GlobalAvgPool2D O O -
tf.keras.layers.GlobalAvgPool3D O O -
tf.keras.layers.GlobalMaxPool1D O O -
tf.keras.layers.GlobalMaxPool2D O O -
tf.keras.layers.GlobalMaxPool3D O O -
tf.keras.layers.GlobalMaxPooling1D O O -
tf.keras.layers.GlobalMaxPooling2D O O -
tf.keras.layers.GlobalMaxPooling3D O O -
tf.keras.layers.LayerNormalization O O -
tf.keras.layers.LeakyReLU O O -
tf.keras.layers.LocallyConnected1D O O -
tf.keras.layers.Masking O - -
tf.keras.layers.MaxPool1D O O -
tf.keras.layers.MaxPool2D O O -
tf.keras.layers.MaxPool3D O O -
tf.keras.layers.MaxPooling1D O O -
tf.keras.layers.MaxPooling2D O O -
tf.keras.layers.MaxPooling3D O O -
tf.keras.layers.Maximum O O -
tf.keras.layers.Normalization O O -
tf.keras.layers.PReLU O O -
tf.keras.layers.Permute O O -
tf.keras.layers.ReLU O O -
tf.keras.layers.RepeatVector O - -
tf.keras.layers.Rescaling O O -
tf.keras.layers.Reshape O O -
tf.keras.layers.SeparableConv2D O O -
tf.keras.layers.SeparableConvolution2D O O -
tf.keras.layers.Softmax O O -
tf.keras.layers.ThresholdedReLU O - -
tf.keras.layers.UpSampling1D O O -
tf.keras.layers.UpSampling2D O O -
tf.keras.layers.UpSampling3D O O -
tf.keras.layers.ZeroPadding1D O O -
tf.keras.layers.ZeroPadding2D O O -
tf.keras.layers.ZeroPadding3D O O -
tf.keras.layers.add O O -
tf.keras.layers.concatenate O O -
tf.keras.layers.minimum O O -
tf.keras.layers.multiply O O -
tf.keras.layers.subtract O O -
tf.less O - -
tf.less_equal O - -
tf.linalg.l2_normalize O O -
tf.linalg.matmul O O -
tf.linalg.matrix_transpose O O -
tf.linalg.matvec O O -
tf.linalg.norm O O -
tf.linalg.normalize O O -
tf.linspace O O -
tf.logical_and O - -
tf.logical_or O - -
tf.math.abs O O -
tf.math.acos O - -
tf.math.acosh O - -
tf.math.add O O -
tf.math.add_n O O -
tf.math.argmax O - -
tf.math.argmin O - -
tf.math.asin O - -
tf.math.asinh O - -
tf.math.atan O - -
tf.math.atanh O - -
tf.math.ceil O O -
tf.math.cos O - -
tf.math.cosh O - -
tf.math.count_nonzero O - -
tf.math.divide O O -
tf.math.equal O - -
tf.math.exp O O -
tf.math.expm1 O O -
tf.math.floor O O -
tf.math.floordiv O - -
tf.math.floormod O - -
tf.math.greater O - -
tf.math.greater_equal O - -
tf.math.l2_normalize O O -
tf.math.less O - -
tf.math.less_equal O - -
tf.math.log O O -
tf.math.log1p O O -
tf.math.log_sigmoid O O -
tf.math.log_softmax O O -
tf.math.logical_and O - -
tf.math.logical_or O - -
tf.math.logical_xor O - -
tf.math.maximum O O -
tf.math.minimum O O -
tf.math.mod O - -
tf.math.multiply O O -
tf.math.not_equal O - -
tf.math.pow O O -
tf.math.reduce_all O - -
tf.math.reduce_any O - -
tf.math.reduce_euclidean_norm O O -
tf.math.reduce_logsumexp O - -
tf.math.reduce_max O O -
tf.math.reduce_mean O O -
tf.math.reduce_min O O -
tf.math.reduce_prod O O -
tf.math.reduce_std O O -
tf.math.reduce_sum O O -
tf.math.reduce_variance O O -
tf.math.rint O O -
tf.math.round O O -
tf.math.rsqrt O O -
tf.math.sigmoid O O -
tf.math.sign O O -
tf.math.sin O - -
tf.math.sinh O - -
tf.math.softmax O O -
tf.math.softplus O O -
tf.math.softsign O O -
tf.math.sqrt O O -
tf.math.square O O -
tf.math.subtract O O -
tf.math.tan O - -
tf.math.tanh O O -
tf.math.top_k O - -
tf.math.truediv O O -
tf.matmul O O -
tf.maximum O O -
tf.minimum O O -
tf.multiply O O -
tf.nest.flatten O O -
tf.nn.batch_normalization O O -
tf.nn.bias_add O O -
tf.nn.conv2d O O -
tf.nn.depth_to_space O - -
tf.nn.elu O O -
tf.nn.gelu O O -
tf.nn.l2_normalize O O -
tf.nn.leaky_relu O O -
tf.nn.log_softmax O O -
tf.nn.moments O O -
tf.nn.relu O O -
tf.nn.relu6 O O -
tf.nn.sigmoid O O -
tf.nn.silu O O -
tf.nn.softmax O O -
tf.nn.softplus O O -
tf.nn.softsign O O -
tf.nn.space_to_depth O O -
tf.nn.sufficient_statistics O O -
tf.nn.swish O O -
tf.nn.tanh O O -
tf.nn.top_k O - -
tf.norm O O Accelerate for 'ord'=1, 2, 'euclidean', 'fro', and np.inf
tf.not_equal O - -
tf.one_hot O - -
tf.ones O O -
tf.ones_like O O -
tf.pad O O Accelerate for constant padding
tf.pow O O Accelerate for scalar power
tf.ragged.constant O O -
tf.range O O -
tf.rank O O -
tf.realdiv O O -
tf.reduce_all O - -
tf.reduce_any O - -
tf.reduce_logsumexp O - -
tf.reduce_max O O -
tf.reduce_mean O O -
tf.reduce_min O O -
tf.reduce_prod O O -
tf.reduce_sum O O -
tf.repeat O - -
tf.reshape O O -
tf.reverse O O -
tf.round O O -
tf.shape O O -
tf.shape_n O O -
tf.sigmoid O O -
tf.sign O O -
tf.sin O - -
tf.sinh O - -
tf.size O O -
tf.slice O O -
tf.split O O -
tf.sqrt O O -
tf.square O O -
tf.squeeze O O -
tf.stack O O -
tf.subtract O O -
tf.tan O - -
tf.tanh O O -
tf.tile O - -
tf.transpose O O -
tf.truediv O O -
tf.truncatemod O - -
tf.unstack O O -
tf.zeros O O -
tf.zeros_like O O -