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Commit 1f88e209 authored by Michael Butler's avatar Michael Butler Committed by Android (Google) Code Review
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Merge "Sync NNAPI Operand and Operation documentation fixes" into pi-dev

parents c6567b1a 25f3ad32

current.txt

+4 −3
Original line number Diff line number Diff line
@@ -241,11 +241,11 @@ a432d6d9200248dc2126827bcd6cdea31dd65eff39b939f64585d27d915a5857 android.hardwar 
86ba9c03978b79a742e990420bc5ced0673d25a939f82572996bef92621e2014 android.hardware.cas@1.0::IMediaCasService

503da837d1a67cbdb7c08a033e927e5430ae1b159d98bf72c6336b4dcc5e76f5 android.hardware.cas.native@1.0::types

619600109232ed64b827c8a11beed8070b1827ae464547d7aa146cf0473b4bca android.hardware.cas.native@1.0::IDescrambler

246a56d37d57a47224562c9d077b4a2886ce6242b9311bd98a17325944c280d7 android.hardware.neuralnetworks@1.0::types

93eb3757ceaf21590fa4cd1d4a7dfe3b3794af5396100a6d25630879352abce9 android.hardware.neuralnetworks@1.0::IDevice

f66f9a38541bf92001d3adcce678cd7e3da2262124befb460b1c9aea9492813b android.hardware.neuralnetworks@1.0::IExecutionCallback

953607822954435874f4b81686440a604e2a88cdd2d9164c6293f3d5772510d7 android.hardware.neuralnetworks@1.0::IPreparedModel

73e03573494ba96f0e711ab7f1956c5b2d54c3da690cd7ecf4d6d0f287447730 android.hardware.neuralnetworks@1.0::IPreparedModelCallback

246a56d37d57a47224562c9d077b4a2886ce6242b9311bd98a17325944c280d7 android.hardware.neuralnetworks@1.0::types

f4945e397b5dea41bb64518dfde59be71245d8a125fd1e0acffeb57ac7b08fed android.hardware.thermal@1.1::IThermal

c8bc853546dd55584611def2a9fa1d99f657e3366c976d2f60fe6b8aa6d2cb87 android.hardware.thermal@1.1::IThermalCallback
@@ -259,7 +259,8 @@ fb92e2b40f8e9d494e8fd3b4ac18499a3216342e7cff160714c3bbf3660b6e79 android.hardwar 
251594ea9b27447bfa005ebd806e58fb0ae4aad84a69938129c9800ec0c64eda android.hardware.gnss@1.0::IGnssMeasurementCallback

4e7169919d24fbe5573e5bcd683d0bd7abf553a4e6c34c41f9dfc1e12050db07 android.hardware.gnss@1.0::IGnssNavigationMessageCallback

5804ca86611d72e5481f022b3a0c1b334217f2e4988dad25730c42af2d1f4d1c android.hardware.neuralnetworks@1.0::IDevice

6721fc5b64d997f3eda15b762a0dd9f3fa414926219dbca58312972d565b4bee android.hardware.neuralnetworks@1.0::types

12e8dca4ab7d8aadd0ef8f1b438021938e2396139e85db2ed65783b08800aa52 android.hardware.neuralnetworks@1.0::IExecutionCallback

702f9a4cd3b7486a4b04f7155b737757ac2ca4b3548976d5782ad3cae9ff9780 android.hardware.neuralnetworks@1.0::types

d4840db8efabdf1e4b344fc981cd36e5fe81a39aff6e199f6d06c1c8da413efd android.hardware.radio@1.0::types

b280c4704dfcc548a9bf127b59b7c3578f460c50cce70a06b66fe0df8b27cff0 android.hardware.wifi@1.0::types
@@ -338,7 +339,7 @@ b8c7ed58aa8740361e63d0ce9e7c94227572a629f356958840b34809d2393a7c android.hardwar 
4a2c0dc82780e6c90731725a103feab8ab6ecf85a64e049b9cbd2b2c61620fe1 android.hardware.media.bufferpool@1.0::IConnection

6aef1218e5949f867b0104752ac536c1b707222a403341720de90141df129e3e android.hardware.media.bufferpool@1.0::types

3e4d8e0085ebe8549efb8ad4b8b400a141a3fa3f47ae23696b3e05a1612eb003 android.hardware.neuralnetworks@1.1::IDevice

e808a6f61cd7b47887c599d8843e67a2dcbf4ec5aadd5d22fdce93020070ef1b android.hardware.neuralnetworks@1.1::types

50db076b03a6760557fc60ef433ba9dd2ff983cf3305eeb504b0fff3eaa604ff android.hardware.neuralnetworks@1.1::types

8d3d86da0bfa4bf070970d8303c659f67f35d670c287d45a3f542e4fedadd578 android.hardware.nfc@1.1::INfc

e85f566698d2a2c28100e264fcf2c691a066756ddf8dd341d009ff50cfe10614 android.hardware.nfc@1.1::INfcClientCallback

5e278fcaa3287d397d8eebe1c22aaa28150f5caae1cf9381cd6dc32cb37899c5 android.hardware.nfc@1.1::types

neuralnetworks/1.0/IExecutionCallback.hal

+1 −1
Original line number Diff line number Diff line
@@ -28,7 +28,7 @@ interface IExecutionCallback { 
     * ErrorStatus resulting from the execution. If the asynchronous task

     * is not launched, notify must be invoked with the appropriate error.

     *

     * @return param Error status returned from launching the asynchronous task

     * @param status Error status returned from launching the asynchronous task

     *               (if the launch fails) or from the asynchronous task itself

     *               (if the launch succeeds). Must be:

     *               - NONE if the asynchronous execution was successful

neuralnetworks/1.0/types.hal

+633 −357

File changed.

Preview size limit exceeded, changes collapsed.

neuralnetworks/1.1/types.hal

+73 −53
Original line number Diff line number Diff line
@@ -27,25 +27,24 @@ import @1.0::PerformanceInfo; 
 */

enum OperationType : @1.0::OperationType {

    /**

     * BatchToSpace for N-D tensors.

     * BatchToSpace for N-dimensional tensors.

     *

     * This operation reshapes the "batch" dimension 0 into M + 1 dimensions of shape

     * This operation reshapes the batch dimension (dimension 0) into M + 1 dimensions of shape

     * block_shape + [batch], interleaves these blocks back into the grid defined by the

     * spatial dimensions [1, ..., M], to obtain a result with the same rank as the input.

     * The spatial dimensions of this intermediate result are then optionally cropped

     * according to the amount to crop to produce the output.

     *

     * This is the reverse of SpaceToBatch.

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor rank: up to 4

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor rank: 4

     *

     * Inputs:

     * 0: An n-D tensor, specifying the input.

     * 0: An n-D tensor, specifying the tensor to be reshaped

     * 1: A 1-D Tensor of type TENSOR_INT32, the block sizes for each spatial dimension of the

     *    input tensor. All values must be >= 1.

     * 2: A 1-D Tensor of type TENSOR_INT32, the amount to crop for each spatial diemension of the

     *    input tensor. All values must be >= 0.

     *

     * Outputs:

     * 0: A tensor of the same type as input0.
@@ -53,9 +52,9 @@ enum OperationType : @1.0::OperationType { 
    BATCH_TO_SPACE_ND = 29,



    /**

     * Divides the second tensor from the first tensor, element-wise.

     * Element-wise division of two tensors.

     *

     * Takes two input tensors of identical OperandType and compatible dimensions. The output

     * Takes two input tensors of identical type and compatible dimensions. The output

     * is the result of dividing the first input tensor by the second, optionally

     * modified by an activation function.

     *
@@ -71,7 +70,9 @@ enum OperationType : @1.0::OperationType { 
     *     input2.dimension = {5, 4, 3, 1}

     *     output.dimension = {5, 4, 3, 2}

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     *

     * Supported tensor rank: up to 4

     *

     * Inputs:
@@ -88,15 +89,17 @@ enum OperationType : @1.0::OperationType { 
    /**

     * Computes the mean of elements across dimensions of a tensor.

     *

     * Reduces input tensor along the dimensions given in axis. Unless keep_dims is true,

     * the rank of the tensor is reduced by 1 for each entry in axis. If keep_dims is

     * true, the reduced dimensions are retained with length 1.

     * Reduces the input tensor along the given dimensions to reduce. Unless keep_dims

     * is true, the rank of the tensor is reduced by 1 for each entry in axis.

     * If keep_dims is true, the reduced dimensions are retained with length 1.

     *

     * If dimensions to reduce have no entries, all dimensions are reduced, and a tensor with

     * a single element is returned.

     *

     * If axis has no entries, all dimensions are reduced, and a tensor with a single

     * element is returned.

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor rank: up to 4

     *

     * Inputs:
@@ -115,14 +118,18 @@ enum OperationType : @1.0::OperationType { 
     *

     * This operation pads a tensor according to the specified paddings.

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor rank: up to 4

     *

     * Inputs:

     * 0: An n-D tensor, specifying the input.

     * 1: A 2-D Tensor of type TENSOR_INT32. The paddings, before and after for each spatial dimension

     *    of the input tensor.

     * 0: An n-D tensor, specifying the tensor to be padded.

     * 1: A 2-D Tensor of type TENSOR_INT32, the paddings for each spatial dimension of the

     *    input tensor. The shape of the tensor must be {rank(input0), 2}.

     *    padding[i, 0] specifies the number of element to be padded in the front of dimension i.

     *    padding[i, 1] specifies the number of element to be padded after the end of dimension i.

     *

     * Outputs:

     * 0: A tensor of the same type as input0.
@@ -130,7 +137,7 @@ enum OperationType : @1.0::OperationType { 
    PAD = 32,



    /**

     * SpaceToBatch for N-D tensors.

     * SpaceToBatch for N-Dimensional tensors.

     *

     * This operation divides "spatial" dimensions [1, ..., M] of the input into a grid of blocks

     * of shape block_shape, and interleaves these blocks with the "batch" dimension (0) such that
@@ -139,16 +146,20 @@ enum OperationType : @1.0::OperationType { 
     * batch position. Prior to division into blocks, the spatial dimensions of the input are

     * optionally zero padded according to paddings.

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor rank: up to 4

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor rank: 4

     *

     * Inputs:

     * 0: An n-D tensor, specifying the input.

     * 1: A 1-D Tensor of type TENSOR_INT32, the block sizes for each spatial dimension of the

     *    input tensor. All values must be >= 1.

     * 2: A 2-D Tensor of type TENSOR_INT32, the paddings for each spatial diemension of the

     *    input tensor. All values must be >= 0.

     *    input tensor. All values must be >= 0. The shape of the tensor must be {rank(input0), 2}.

     *    padding[i, 0] specifies the number of element to be padded in the front of dimension i.

     *    padding[i, 1] specifies the number of element to be padded after the end of dimension i.

     *

     * Outputs:

     * 0: A tensor of the same type as input0.
@@ -160,17 +171,20 @@ enum OperationType : @1.0::OperationType { 
     *

     * Given a tensor input, this operation returns a tensor of the same type with all

     * dimensions of size 1 removed. If you don't want to remove all size 1 dimensions,

     * you can remove specific size 1 dimensions by specifying axis.

     * you can remove specific size 1 dimensions by specifying the axes (input1).

     *

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor rank: up to 4

     *

     * Inputs:

     * 0: An n-D tensor, specifying the input.

     * 1: An 1-D Tensor of type TENSOR_INT32. The dimensions to squeeze. If None (the default),

     *    squeezes all dimensions. If specified, only squeezes the dimensions listed. The dimension

     *    index starts at 0. It is an error to squeeze a dimension that is not 1.

     * 0: An n-D tensor, the tensor to be squeezed.

     * 1: An optional 1-D tensor of type TENSOR_INT32. The dimensions to squeeze. If specified

     *    only squeezes the dimensions listed. Otherwise, squeezes all dimensions.

     *    The dimension index starts at 0. An error must be reported if squeezing a dimension that

     *    is not 1.

     *

     * Outputs:

     * 0: A tensor of the same type as input0. Contains the same data as input, but has one or more
@@ -181,23 +195,25 @@ enum OperationType : @1.0::OperationType { 
    /**

     * Extracts a strided slice of a tensor.

     *

     * This op extracts a slice of size (end-begin)/stride from the given input tensor.

    *  Starting at the location specified by begin the slice continues by adding

     * Roughly speaking, this op extracts a slice of size (end - begin) / stride from the given

     * input tensor. Starting at the location specified by begin the slice continues by adding

     * stride to the index until all dimensions are not less than end. Note that a stride can

     * be negative, which causes a reverse slice.

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor rank: up to 4

     *

     * Inputs:

     * 0: An n-D tensor, specifying the input.

     * 0: An n-D tensor, specifying the tensor to be sliced.

     * 1: A 1-D Tensor of type TENSOR_INT32, the starts of the dimensions of the input

     *    tensor to be sliced.

     *    tensor to be sliced. The length must be of rank(input0).

     * 2: A 1-D Tensor of type TENSOR_INT32, the ends of the dimensions of the input

     *    tensor to be sliced.

     *    tensor to be sliced. The length must be of rank(input0).

     * 3: A 1-D Tensor of type TENSOR_INT32, the strides of the dimensions of the input

     *    tensor to be sliced.

     *    tensor to be sliced. The length must be of rank(input0).

     *

     * Outputs:

     * 0: A tensor of the same type as input0.
@@ -205,7 +221,7 @@ enum OperationType : @1.0::OperationType { 
    STRIDED_SLICE = 35,



    /**

     * Subtracts the second tensor from the first tensor, element-wise.

     * Element-wise subtraction of two tensors.

     *

     * Takes two input tensors of identical type and compatible dimensions. The output

     * is the result of subtracting the second input tensor from the first one, optionally
@@ -223,7 +239,9 @@ enum OperationType : @1.0::OperationType { 
     *     input2.dimension = {5, 4, 3, 1}

     *     output.dimension = {5, 4, 3, 2}

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     *

     * Supported tensor rank: up to 4

     *

     * Inputs:
@@ -240,18 +258,20 @@ enum OperationType : @1.0::OperationType { 
    /**

     * Transposes the input tensor, permuting the dimensions according to the perm tensor.

     *

     * The returned tensor's dimension i must correspond to the input dimension perm[i].

     * The returned tensor's dimension i corresponds to the input dimension perm[i].

     * If perm is not given, it is set to (n-1...0), where n is the rank of the input tensor.

     * Hence by default, this operation performs a regular matrix transpose on 2-D input Tensors.

     *

     * Supported tensor types: {@link OperandType::TENSOR_FLOAT32}

     *                         {@link OperandType::TENSOR_QUANT8_ASYMM}

     * Supported tensor types:

     * * {@link OperandType::TENSOR_FLOAT32}

     * * {@link OperandType::TENSOR_QUANT8_ASYMM}

     *

     * Supported tensor rank: up to 4

     *

     * Inputs:

     * 0: An n-D tensor, specifying the input.

     * 1: A 1-D Tensor of type TENSOR_INT32, the permutation of the dimensions of the input

     *    tensor.

     * 0: An n-D tensor, specifying the tensor to be transposed.

     * 1: An optional 1-D Tensor of type TENSOR_INT32, the permutation of the dimensions of the

     *    input tensor.

     *

     * Outputs:

     * 0: A tensor of the same type as input0.