Sync docs with NeuralNetworks.h
Bug: 115855152 Test: none Change-Id: I15b5207f3ffbea57a4c8313ce744a22ce72b402e
This commit is contained in:
Slava Shklyaev
Przemyslaw Szczepaniak
parent
96e08aa749
commit
af528bc51c
4 changed files with 121 additions and 34 deletions
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@ -387,8 +387,10 @@ cd4330c3196bda1d642a32abfe23a7d64ebfbda721940643af6867af3b3f0aa9 android.hardwar
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# ABI preserving changes to HALs during Android Q
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da33234403ff5d60f3473711917b9948e6484a4260b5247acdafb111193a9de2 android.hardware.configstore@1.0::ISurfaceFlingerConfigs
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574e8f1499436fb4075894dcae0b36682427956ecb114f17f1fe22d116a83c6b android.hardware.neuralnetworks@1.0::IPreparedModel
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1a5ae9793223658174258b523763c557abad6fb917df0b8e3cc097fc89035811 android.hardware.neuralnetworks@1.0::types
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4310eb8272f085914952f3bfb73a8f8bb477a80e8b93596f0ea5acb58546b66d android.hardware.neuralnetworks@1.1::types
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1fb32361286b938d48a55c2539c846732afce0b99fe08590f556643125bc13d3 android.hardware.neuralnetworks@1.0::types
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e22e8135d061d0e9c4c1a70c25c19fdba10f4d3cda9795ef25b6392fc520317c android.hardware.neuralnetworks@1.1::types
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810b03825c633b21982871a8aa690db94285947fca71881de71bf293ad0aa9c5 android.hardware.neuralnetworks@1.2::types
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79f3820a02f37bb0f84bca1a07900fd5bd819ec5a60ed14b205e1dc5e24a51b2 android.hardware.neuralnetworks@1.2::IDevice
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1d4a5776614c08b5d794a5ec5ab04697260cbd4b3441d5935cd53ee71d19da02 android.hardware.radio@1.0::IRadioResponse
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271187e261b30c01a33011aea257c07a2d2f05b72943ebee89e973e997849973 android.hardware.radio@1.0::types
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1d19720d4fd38b1095f0f555a4bd92b3b12c9b1d0f560b0e9a474cd6dcc20db6 android.hardware.radio@1.2::IRadio
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@ -68,6 +68,7 @@ enum OperandType : int32_t {
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* The type of an operation in a model.
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*/
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enum OperationType : int32_t {
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/**
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* Adds two tensors, element-wise.
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*
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@ -105,6 +106,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The sum, a tensor of the same {@link OperandType} as input0.
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*
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* Available since API level 27.
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*/
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ADD = 0,
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@ -116,8 +119,10 @@ enum OperationType : int32_t {
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*
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* The values in the output tensor are computed as:
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*
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* output[batch, row, col, channel] =
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* sum_{i, j}(input[batch, row + i, col + j, channel]) / sum(1)
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* output[b, i, j, channel] =
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* sum_{di, dj}(
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* input[b, strides[1] * i + di, strides[2] * j + dj, channel]
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* ) / sum(1)
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*
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* Supported tensor {@link OperandType}:
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* * {@link OperandType::TENSOR_FLOAT32}
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@ -171,7 +176,9 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output 4-D tensor, of shape
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[batches, out_height, out_width, depth].
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* [batches, out_height, out_width, depth].
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*
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* Available since API level 27.
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*/
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AVERAGE_POOL_2D = 1,
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@ -198,6 +205,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output, a tensor of the same {@link OperandType} as the input
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* tensors. The output shape is [D0, D1, ..., sum(Daxis(i)), ..., Dm].
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*
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* Available since API level 27.
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*/
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CONCATENATION = 2,
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@ -213,12 +222,11 @@ enum OperationType : int32_t {
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*
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* The values in the output tensor are computed as:
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*
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* output[batch, row, col, channel] =
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* sum_{i, j} (
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* input[batch, row + i, col + j, k] *
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* filter[channel, row + i, col + j, k] +
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* bias[channel]
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* )
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* output[b, i, j, channel] =
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* sum_{di, dj, k} (
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* input[b, strides[1] * i + di, strides[2] * j + dj, k] *
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* filter[channel, di, dj, k]
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* ) + bias[channel]
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*
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* Supported tensor {@link OperandType}:
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* * {@link OperandType::TENSOR_FLOAT32}
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@ -274,7 +282,7 @@ enum OperationType : int32_t {
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* * 4: An {@link OperandType::INT32} scalar, specifying the stride when
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* walking through input in the ‘width’ dimension.
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* * 5: An {@link OperandType::INT32} scalar, specifying the stride when
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* walking through input in the ‘height’ dimension.
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* walking through input in the ‘height’ dimension.
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* * 6: An {@link OperandType::INT32} scalar, and has to be one of the
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* {@link FusedActivationFunc} values. Specifies the activation to
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* invoke on the result.
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@ -284,6 +292,8 @@ enum OperationType : int32_t {
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* [batches, out_height, out_width, depth_out]. For output tensor of
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* {@link OperandType::TENSOR_QUANT8_ASYMM}, the following condition
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* must be satisfied: output_scale > input_scale * filter_scale.
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*
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* Available since API level 27.
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*/
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CONV_2D = 3,
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@ -307,7 +317,7 @@ enum OperationType : int32_t {
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* sum_{di, dj} (
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* input[b, strides[1] * i + di, strides[2] * j + dj, k] *
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* filter[1, di, dj, k * channel_multiplier + q]
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* )
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* ) + bias[k * channel_multiplier + q]
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*
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* Supported tensor {@link OperandType}:
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* * {@link OperandType::TENSOR_FLOAT32}
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@ -375,6 +385,8 @@ enum OperationType : int32_t {
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* [batches, out_height, out_width, depth_out]. For output tensor of
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* {@link OperandType::TENSOR_QUANT8_ASYMM}, the following condition
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* must be satisfied: output_scale > input_scale * filter_scale.
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*
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* Available since API level 27.
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*/
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DEPTHWISE_CONV_2D = 4,
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@ -409,6 +421,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output 4-D tensor, of shape [batch, height*block_size,
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* width*block_size, depth/(block_size*block_size)].
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*
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* Available since API level 27.
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*/
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DEPTH_TO_SPACE = 5,
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@ -430,6 +444,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output tensor of same shape as input0, but with
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* {@link OperandType::TENSOR_FLOAT32}.
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*
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* Available since API level 27.
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*/
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DEQUANTIZE = 6,
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@ -463,6 +479,8 @@ enum OperationType : int32_t {
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* * 0: A n-D tensor with the same rank and shape as the Values
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* tensor, except for the first dimension which has the same size
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* as Lookups' only dimension.
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*
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* Available since API level 27.
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*/
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EMBEDDING_LOOKUP = 7,
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@ -480,6 +498,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output tensor, of the same {@link OperandType} and dimensions as
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* the input tensor.
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*
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* Available since API level 27.
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*/
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FLOOR = 8,
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@ -523,6 +543,8 @@ enum OperationType : int32_t {
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* tensor of {@link OperandType::TENSOR_QUANT8_ASYMM}, the following
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* condition must be satisfied:
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* output_scale > input_scale * filter_scale.
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*
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* Available since API level 27.
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*/
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FULLY_CONNECTED = 9,
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@ -571,6 +593,8 @@ enum OperationType : int32_t {
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* Stored as {@link OperandType::TENSOR_QUANT8_ASYMM} with offset 0
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* and scale 1.0f.
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* A non-zero byte represents True, a hit. A zero indicates otherwise.
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*
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* Available since API level 27.
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*/
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HASHTABLE_LOOKUP = 10,
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@ -598,6 +622,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output 4-D tensor, of the same shape as input
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* [batches, height, width, depth].
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*
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* Available since API level 27.
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*/
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L2_NORMALIZATION = 11,
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@ -609,8 +635,8 @@ enum OperationType : int32_t {
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*
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* The values in the output tensor are computed as:
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*
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* output[batch, row, col, channel] =
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* sqrt(sum_{i, j} pow(input[batch, row + i, col + j, channel], 2) /
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* output[b, i, j, c] =
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* sqrt(sum_{di, dj} pow(input[b, strides[1] * i + di, strides[2] * j + dj, c], 2) /
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* sum(1))
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*
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* Supported tensor {@link OperandType}:
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@ -664,6 +690,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output 4-D tensor, of shape
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* [batches, out_height, out_width, depth].
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*
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* Available since API level 27.
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*/
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L2_POOL_2D = 12,
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@ -700,6 +728,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output tensor of same shape as input0.
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*
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* Available since API level 27.
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*/
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LOCAL_RESPONSE_NORMALIZATION = 13,
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@ -723,6 +753,8 @@ enum OperationType : int32_t {
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* * 0: The output tensor of same shape as input0.
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* For {@link OperandType::TENSOR_QUANT8_ASYMM},
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* the scale must be 1.f / 256 and the zeroPoint must be 0.
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*
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* Available since API level 27.
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*/
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LOGISTIC = 14,
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@ -758,6 +790,8 @@ enum OperationType : int32_t {
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* If the projection type is Dense:
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* Output.Dim == { Tensor[0].Dim[0] * Tensor[0].Dim[1] }
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* A flattened tensor that represents projected bit vectors.
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*
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* Available since API level 27.
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*/
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LSH_PROJECTION = 15,
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@ -952,6 +986,8 @@ enum OperationType : int32_t {
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* A 2-D tensor of {@link OperandType::TENSOR_FLOAT32}, of shape
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* [batch_size, output_size]. This is effectively the same as the
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* current “output state (out)” value.
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*
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* Available since API level 27.
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*/
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LSTM = 16,
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@ -963,8 +999,10 @@ enum OperationType : int32_t {
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*
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* The values in the output tensor are computed as:
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*
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* output[batch, row, col, channel] =
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* max_{i, j} (input[batch, row + i, col + j, channel])
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* output[b, i, j, channel] =
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* max_{di, dj} (
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* input[b, strides[1] * i + di, strides[2] * j + dj, channel]
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* )
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*
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* Supported tensor {@link OperandType}:
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* * {@link OperandType::TENSOR_FLOAT32}
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@ -1018,6 +1056,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output 4-D tensor, of shape
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* [batches, out_height, out_width, depth].
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*
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* Available since API level 27.
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*/
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MAX_POOL_2D = 17,
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@ -1055,6 +1095,8 @@ enum OperationType : int32_t {
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* For output tensor of {@link OperandType::TENSOR_QUANT8_ASYMM},
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* the following condition must be satisfied:
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* output_scale > input1_scale * input2_scale.
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*
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* Available since API level 27.
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*/
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MUL = 18,
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@ -1076,6 +1118,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output tensor of same shape as input0.
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*
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* Available since API level 27.
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*/
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RELU = 19,
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@ -1097,6 +1141,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output tensor of same shape as input0.
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*
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* Available since API level 27.
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*/
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RELU1 = 20,
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@ -1118,6 +1164,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output tensor of same shape as input0.
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*
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* Available since API level 27.
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*/
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RELU6 = 21,
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@ -1141,6 +1189,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output tensor, of shape specified by the input shape.
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*
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* Available since API level 27.
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*/
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RESHAPE = 22,
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@ -1167,6 +1217,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output 4-D tensor, of shape
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* [batches, new_height, new_width, depth].
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*
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* Available since API level 27.
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*/
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RESIZE_BILINEAR = 23,
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@ -1222,6 +1274,8 @@ enum OperationType : int32_t {
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* A 2-D tensor of {@link OperandType::TENSOR_FLOAT32}, of shape
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* [batch_size, num_units]. This is effectively the same as the
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* current state value.
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*
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* Available since API level 27.
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*/
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RNN = 24,
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@ -1251,6 +1305,8 @@ enum OperationType : int32_t {
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* * 0: The output tensor of same shape as input0.
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* For {@link OperandType::TENSOR_QUANT8_ASYMM},
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* the scale must be 1.f / 256 and the zeroPoint must be 0.
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*
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* Available since API level 27.
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*/
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SOFTMAX = 25,
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@ -1284,6 +1340,8 @@ enum OperationType : int32_t {
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* Outputs:
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* * 0: The output 4-D tensor, of shape [batches, height/block_size,
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* width/block_size, depth_in*block_size*block_size].
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*
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* Available since API level 27.
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*/
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SPACE_TO_DEPTH = 26,
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@ -1361,7 +1419,9 @@ enum OperationType : int32_t {
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* [batch_size, (memory_size - 1) * num_units * rank].
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* * 1: output.
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* A 2-D tensor of {@link OperandType::TENSOR_FLOAT32}, of shape
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* [batch_size, num_units].
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* [batch_size, num_units].
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*
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* Available since API level 27.
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*/
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SVDF = 27,
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@ -1382,6 +1442,8 @@ enum OperationType : int32_t {
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*
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* Outputs:
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* * 0: The output tensor of same shape as input0.
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*
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* Available since API level 27.
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*/
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TANH = 28,
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@ -26,6 +26,7 @@ import @1.0::PerformanceInfo;
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* The type of an operation in a model.
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*/
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enum OperationType : @1.0::OperationType {
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/**
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* BatchToSpace for N-dimensional tensors.
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*
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@ -50,6 +51,8 @@ enum OperationType : @1.0::OperationType {
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*
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* Outputs:
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* * 0: A tensor of the same {@link OperandType} as input0.
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*
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* Available since API level 28.
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*/
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BATCH_TO_SPACE_ND = 29,
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@ -88,6 +91,8 @@ enum OperationType : @1.0::OperationType {
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*
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* Outputs:
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* * 0: A tensor of the same {@link OperandType} as input0.
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*
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* Available since API level 28.
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*/
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DIV = 30,
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@ -118,6 +123,8 @@ enum OperationType : @1.0::OperationType {
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*
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* Outputs:
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* * 0: A tensor of the same {@link OperandType} as input0.
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*
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* Available since API level 28.
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*/
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MEAN = 31,
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@ -150,6 +157,8 @@ enum OperationType : @1.0::OperationType {
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* of the padding:
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* output0.dimension[i] =
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* padding[i, 0] + input0.dimension[i] + padding[i, 1]
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*
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* Available since API level 28.
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*/
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PAD = 32,
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@ -185,6 +194,8 @@ enum OperationType : @1.0::OperationType {
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*
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* Outputs:
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* * 0: A tensor of the same {@link OperandType} as input0.
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*
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* Available since API level 28.
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*/
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SPACE_TO_BATCH_ND = 33,
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@ -214,6 +225,8 @@ enum OperationType : @1.0::OperationType {
|
|||
* * 0: A tensor of the same {@link OperandType} as input0. Contains the
|
||||
* same data as input, but has one or more dimensions of size 1
|
||||
* removed.
|
||||
*
|
||||
* Available since API level 28.
|
||||
*/
|
||||
SQUEEZE = 34,
|
||||
|
||||
|
|
@ -234,28 +247,32 @@ enum OperationType : @1.0::OperationType {
|
|||
*
|
||||
* Inputs:
|
||||
* * 0: An n-D tensor, specifying the tensor to be sliced.
|
||||
* * 1: A 1-D Tensor of {@link OperandType::TENSOR_INT32}, the starts of
|
||||
* the dimensions of the input tensor to be sliced. The length must be
|
||||
* of rank(input0).
|
||||
* * 2: A 1-D Tensor of {@link OperandType::TENSOR_INT32}, the ends of
|
||||
* the dimensions of the input tensor to be sliced. The length must be
|
||||
* of rank(input0).
|
||||
* * 3: A 1-D Tensor of {@link OperandType::TENSOR_INT32}, the strides of
|
||||
* the dimensions of the input tensor to be sliced. The length must be
|
||||
* of rank(input0).
|
||||
* * 4: An {@link OperandType::INT32} scalar, begin_mask. If the ith bit
|
||||
* * 1: begin, a 1-D tensor of {@link OperandType::TENSOR_INT32}. The
|
||||
* starts of the dimensions of the input tensor to be sliced. The
|
||||
* length must be of rank(input0).
|
||||
* * 2: end, a 1-D tensor of {@link OperandType::TENSOR_INT32}. The
|
||||
* ends of the dimensions of the input tensor to be sliced. The length
|
||||
* must be of rank(input0).
|
||||
* * 3: strides, a 1-D tensor of {@link OperandType::TENSOR_INT32}. The
|
||||
* strides of the dimensions of the input tensor to be sliced. The
|
||||
* length must be of rank(input0). The entries must be non-zero.
|
||||
* * 4: begin_mask, an {@link OperandType::INT32} scalar. If the ith bit
|
||||
* of begin_mask is set, begin[i] is ignored and the fullest possible
|
||||
* range in that dimension is used instead.
|
||||
* * 5: An {@link OperandType::INT32} scalar, end_mask. If the ith bit of
|
||||
* * 5: end_mask, an {@link OperandType::INT32} scalar. If the ith bit of
|
||||
* end_mask is set, end[i] is ignored and the fullest possible range in
|
||||
* that dimension is used instead.
|
||||
* * 6: An {@link OperandType::INT32} scalar, shrink_axis_mask. An int32
|
||||
* mask. If the ith bit of shrink_axis_mask is set, it implies that the
|
||||
* ith specification shrinks the dimensionality by 1. A slice of size 1
|
||||
* starting from begin[i] in the dimension must be preserved.
|
||||
* * 6: shrink_axis_mask, an {@link OperandType::INT32} scalar. If the
|
||||
* ith bit of shrink_axis_mask is set, the ith dimension specification
|
||||
* shrinks the dimensionality by 1, taking on the value at index
|
||||
* begin[i]. In this case, the ith specification must define a
|
||||
* slice of size 1, e.g. begin[i] = x, end[i] = x + 1.
|
||||
*
|
||||
* Outputs:
|
||||
* * 0: A tensor of the same {@link OperandType} as input0.
|
||||
* * 0: A tensor of the same {@link OperandType} as input0 and rank (n - k),
|
||||
* where k is the number of bits set in shrink_axis_mask.
|
||||
*
|
||||
* Available since API level 28.
|
||||
*/
|
||||
STRIDED_SLICE = 35,
|
||||
|
||||
|
|
@ -294,6 +311,8 @@ enum OperationType : @1.0::OperationType {
|
|||
*
|
||||
* Outputs:
|
||||
* * 0: A tensor of the same {@link OperandType} as input0.
|
||||
*
|
||||
* Available since API level 28.
|
||||
*/
|
||||
SUB = 36,
|
||||
|
||||
|
|
@ -319,8 +338,11 @@ enum OperationType : @1.0::OperationType {
|
|||
*
|
||||
* Outputs:
|
||||
* * 0: A tensor of the same {@link OperandType} as input0.
|
||||
*
|
||||
* Available since API level 28.
|
||||
*/
|
||||
TRANSPOSE = 37,
|
||||
|
||||
};
|
||||
|
||||
/**
|
||||
|
|
|
|||
|
|
@ -26,6 +26,7 @@ import @1.1::OperationType;
|
|||
* The type of an operation in a model.
|
||||
*/
|
||||
enum OperationType : @1.1::OperationType {
|
||||
|
||||
};
|
||||
|
||||
/**
|
||||
|
|
|
|||
Loading…
Reference in a new issue