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Sync operation docs between NeuralNetworks.h and HAL file am: 66baf74114

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am: e265b746b9

Change-Id: Iafbf27f0c06886f934bb9e3faaa72f0ea76f1312
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Xusong Wang 2019-03-22 17:27:53 -07:00 committed by android-build-merger
commit 094a06c28e
2 changed files with 139 additions and 41 deletions
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@ -450,7 +450,7 @@ b83317b66721241887d2770b5ae95fd5af1e77c5daa7530ecb08fae8892f2b43 android.hardwar
92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
36e1064c869965dee533c537cefbe87e54db8bd8cd45be7e0e93e00e8a43863a android.hardware.neuralnetworks@1.2::IPreparedModel
e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
d734c2441b602da240fa0e9afe3b612cdc9f3ae9c1db13216f957861d0673c5e android.hardware.neuralnetworks@1.2::types
209a5ee694b94328afb2af2768f1fe6a69148e2cbb85ec3c340a36eed818c697 android.hardware.neuralnetworks@1.2::types
cf7a4ba516a638f9b82a249c91fb603042c2d9ca43fd5aad9cf6c0401ed2a5d7 android.hardware.nfc@1.2::INfc
abf98c2ae08bf765db54edc8068e36d52eb558cff6706b6fd7c18c65a1f3fc18 android.hardware.nfc@1.2::types
4cb252dc6372a874aef666b92a6e9529915aa187521a700f0789065c3c702ead android.hardware.power.stats@1.0::IPowerStats

178
neuralnetworks/1.2/types.hal
View file

@ -187,6 +187,10 @@ enum OperationType : int32_t {
* input2.dimension = {5, 4, 3, 1}
* output.dimension = {5, 4, 3, 2}
*
* Since API level 29, generic zero-sized input tensor is supported. Zero
* dimension is only compatible with 0 or 1. The size of the output
* dimension is zero if either of corresponding input dimension is zero.
*
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
* * {@link OperandType::TENSOR_FLOAT32}
@ -236,7 +240,8 @@ enum OperationType : int32_t {
*
* Inputs (explicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the padding on
* the left, in the ‘width’ dimension.
* * 2: An {@link OperandType::INT32} scalar, specifying the padding on
@ -262,7 +267,8 @@ enum OperationType : int32_t {
*
* Inputs (implicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the implicit
* padding scheme, has to be one of the
* following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
@ -309,6 +315,7 @@ enum OperationType : int32_t {
* Before API level 29, all input tensors of
* {@link OperandType::TENSOR_QUANT8_ASYMM}
* must have the same scale and zeroPoint as the output tensor.
* Since API level 29, zero-sized tensors are supported.
* * n: An {@link OperandType::INT32} scalar, specifying the
* concatenation axis.
*
@ -366,7 +373,8 @@ enum OperationType : int32_t {
*
* Inputs (explicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
* specifying the input.
* specifying the input. Since API level 29, zero batches is supported
* for this tensor.
* * 1: A 4-D tensor, of shape
* [depth_out, filter_height, filter_width, depth_in], specifying the
* filter. For tensor of type
@ -413,7 +421,8 @@ enum OperationType : int32_t {
*
* Inputs (implicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth_in],
* specifying the input.
* specifying the input. Since API level 29, zero batches is supported
* for this tensor.
* * 1: A 4-D tensor, of shape
* [depth_out, filter_height, filter_width, depth_in], specifying the
* filter. For tensor of type
@ -675,7 +684,7 @@ enum OperationType : int32_t {
* Supported tensor rank: up to 4
*
* Inputs:
* * 0: A tensor.
* * 0: A tensor. Since API level 29, this tensor may be zero-sized.
*
* Outputs:
* * 0: A tensor with the same shape as input0.
@ -768,7 +777,8 @@ enum OperationType : int32_t {
* [batch_size, input_size], where "input_size" corresponds to the
* number of inputs to the layer, matching the second dimension of
* weights, and "batch_size" is calculated by dividing the number of
* elements by "input_size".
* elements by "input_size". Since API level 29, zero batch_size is
* supported for this tensor.
* * 1: A 2-D tensor, specifying the weights, of shape
* [num_units, input_size], where "num_units" corresponds to the number
* of output nodes.
@ -864,6 +874,7 @@ enum OperationType : int32_t {
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
* * {@link OperandType::TENSOR_FLOAT32}
* * {@link OperandType::TENSOR_QUANT8_ASYMM} (since API level 29)
*
* Supported tensor rank: up to 4
* Tensors with rank less than 4 are only supported since API level 29.
@ -878,6 +889,8 @@ enum OperationType : int32_t {
*
* Outputs:
* * 0: A tensor of the same {@link OperandType} and same shape as input0.
* For {@link OperandType::TENSOR_QUANT8_ASYMM},
* the scale must be 1.f / 128 and the zeroPoint must be 128.
*
* Available since API level 27.
*/
@ -908,7 +921,8 @@ enum OperationType : int32_t {
*
* Inputs (explicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the padding on
* the left, in the ‘width’ dimension.
* * 2: An {@link OperandType::INT32} scalar, specifying the padding on
@ -934,7 +948,8 @@ enum OperationType : int32_t {
*
* Inputs (implicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the implicit
* padding scheme, has to be one of the
* following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
@ -1024,7 +1039,8 @@ enum OperationType : int32_t {
* Supported tensor rank: up to 4.
*
* Inputs:
* * 0: A tensor, specifying the input.
* * 0: A tensor, specifying the input. Since API level 29, this tensor may
* be zero-sized.
*
* Outputs:
* * 0: The output tensor of same shape as input0.
@ -1336,7 +1352,8 @@ enum OperationType : int32_t {
*
* Inputs (explicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the padding on
* the left, in the ‘width’ dimension.
* * 2: An {@link OperandType::INT32} scalar, specifying the padding on
@ -1362,7 +1379,8 @@ enum OperationType : int32_t {
*
* Inputs (implicit padding):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the implicit
* padding scheme, has to be one of the
* following values: {0 (NONE), 1 (SAME), 2 (VALID)}.
@ -1409,6 +1427,10 @@ enum OperationType : int32_t {
* * {@link OperandType::TENSOR_FLOAT32}
* * {@link OperandType::TENSOR_QUANT8_ASYMM}
*
* Since API level 29, generic zero-sized input tensor is supported. Zero
* dimension is only compatible with 0 or 1. The size of the output
* dimension is zero if either of corresponding input dimension is zero.
*
* Supported tensor rank: up to 4
*
* Inputs:
@ -1444,7 +1466,8 @@ enum OperationType : int32_t {
* Supported tensor rank: up to 4.
*
* Inputs:
* * 0: A tensor, specifying the input.
* * 0: A tensor, specifying the input. Since API level 29, this tensor may
* be zero-sized.
*
* Outputs:
* * 0: The output tensor of same shape as input0.
@ -1468,7 +1491,8 @@ enum OperationType : int32_t {
* Supported tensor rank: up to 4.
*
* Inputs:
* * 0: A tensor, specifying the input.
* * 0: A tensor, specifying the input. Since API level 29, this tensor may
* be zero-sized.
*
* Outputs:
* * 0: The output tensor of same shape as input0.
@ -1492,7 +1516,8 @@ enum OperationType : int32_t {
* Supported tensor rank: up to 4.
*
* Inputs:
* * 0: A tensor, specifying the input.
* * 0: A tensor, specifying the input. Since API level 29, this tensor may
* be zero-sized.
*
* Outputs:
* * 0: The output tensor of same shape as input0.
@ -1544,9 +1569,12 @@ enum OperationType : int32_t {
* [batch, height, width, channels]. Alternatively, the data layout could
* be NCHW, the data storage order of: [batch, channels, height, width].
*
* Inputs:
* Both resizing by shape and resizing by scale are supported.
*
* Inputs (resizing by shape):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Since API level 29, zero batches is supported for this
* tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the output
* height of the output tensor.
* * 2: An {@link OperandType::INT32} scalar, specifying the output
@ -1555,6 +1583,24 @@ enum OperationType : int32_t {
* Set to true to specify NCHW data layout for input0 and output0.
* Available since API level 29.
*
* Inputs (resizing by scale, since API level 29):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input. Zero batches is supported for this tensor.
* * 1: A scalar, specifying height_scale, the scaling factor of the height
* dimension from the input tensor to the output tensor. The output
* height is calculated as new_height = floor(height * height_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
* * 2: A scalar, specifying width_scale, the scaling factor of the width
* dimension from the input tensor to the output tensor. The output
* width is calculated as new_width = floor(width * width_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
* * 3: An optional {@link OperandType::BOOL} scalar, default to false.
* Set to true to specify NCHW data layout for input0 and output0.
*
* Outputs:
* * 0: The output 4-D tensor, of shape
* [batches, new_height, new_width, depth].
@ -1640,7 +1686,8 @@ enum OperationType : int32_t {
* Tensors with rank other than 2 or 4 are only supported since API level 29.
*
* Inputs:
* * 0: A 2-D or 4-D tensor, specifying the tensor to be reshaped.
* * 0: A 2-D or 4-D tensor, specifying the tensor to be reshaped. Since
* API level 29, this tensor may be zero-sized.
* * 1: A scalar, specifying the positive scaling factor for the exponent,
* beta. If input0 is of {@link OperandType::TENSOR_FLOAT32} or
* {@link OperandType::TENSOR_QUANT8_ASYMM}, the scalar must be of
@ -1798,7 +1845,8 @@ enum OperationType : int32_t {
* Supported tensor rank: up to 4.
*
* Inputs:
* * 0: A tensor, specifying the input.
* * 0: A tensor, specifying the input. Since API level 29, this tensor may
* be zero-sized.
*
* Outputs:
* * 0: The output tensor of same shape as input0.
@ -1865,6 +1913,10 @@ enum OperationType : int32_t {
* input2.dimension = {5, 4, 3, 1}
* output.dimension = {5, 4, 3, 2}
*
* Since API level 29, generic zero-sized input tensor is supported. Zero
* dimension is only compatible with 0 or 1. The size of the output
* dimension is zero if either of corresponding input dimension is zero.
*
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
* * {@link OperandType::TENSOR_FLOAT32}
@ -2098,6 +2150,10 @@ enum OperationType : int32_t {
* input2.dimension = {5, 4, 3, 1}
* output.dimension = {5, 4, 3, 2}
*
* Since API level 29, generic zero-sized input tensor is supported. Zero
* dimension is only compatible with 0 or 1. The size of the output
* dimension is zero if either of corresponding input dimension is zero.
*
* Supported tensor {@link OperandType}:
* * {@link OperandType::TENSOR_FLOAT16} (since API level 29)
* * {@link OperandType::TENSOR_FLOAT32}
@ -2138,6 +2194,7 @@ enum OperationType : int32_t {
*
* Inputs:
* * 0: An n-D tensor, specifying the tensor to be transposed.
* Since API level 29, this tensor may be zero-sized.
* * 1: An optional 1-D Tensor of {@link OperandType::TENSOR_INT32},
* the permutation of the dimensions of the input tensor.
*
@ -2234,7 +2291,8 @@ enum OperationType : int32_t {
* * 0: A 2-D Tensor of shape [num_rois, 4], specifying the locations of the
* bounding box proposals, each line with format [x1, y1, x2, y2].
* For tensor of type {@link OperandType::TENSOR_QUANT16_ASYMM},
* the zeroPoint must be 0 and the scale must be 0.125.
* the zeroPoint must be 0 and the scale must be 0.125. Zero num_rois
* is supported for this tensor.
* * 1: A 2-D Tensor of shape [num_rois, num_classes * 4], specifying the
* bounding box delta for each region of interest and each class. The
* bounding box deltas are organized in the following order
@ -2243,10 +2301,12 @@ enum OperationType : int32_t {
* and height, dw and dh is the log-scale relative correction factor
* for the width and height. For input0 of type
* {@link OperandType::TENSOR_QUANT16_ASYMM}, this tensor should be
* of {@link OperandType::TENSOR_QUANT8_ASYMM}.
* of {@link OperandType::TENSOR_QUANT8_ASYMM}. Zero num_rois is
* supported for this tensor.
* * 2: An 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
* [num_rois], specifying the batch index of each box. Boxes with
* the same batch index are grouped together.
* the same batch index are grouped together. Zero num_rois is
* supported for this tensor.
* * 3: A 2-D Tensor of shape [batches, 2], specifying the information of
* each image in the batch, each line with format
* [image_height, image_width].
@ -2580,10 +2640,17 @@ enum OperationType : int32_t {
/**
* Greedily selects a subset of bounding boxes in descending order of score.
*
* This op applies hard NMS algorithm to each class. In each loop of
* execution, the box with maximum score gets selected, and any boxes with
* the intersection-over-union (IOU) greater than a threshold are removed
* from the pending set.
* This op applies NMS algorithm to each class. In each loop of execution,
* the box with maximum score gets selected and removed from the pending set.
* The scores of the rest of boxes are lowered according to the
* intersection-over-union (IOU) overlapping with the previously selected
* boxes and a specified NMS kernel method. Any boxes with score less
* than a threshold are removed from the pending set.
*
* Three NMS kernels are supported:
* * Hard: score_new = score_old * (1 if IoU < threshold else 0)
* * Linear: score_new = score_old * (1 if IoU < threshold else 1 - IoU)
* * Gaussian: score_new = score_old * exp(- IoU^2 / sigma)
*
* Axis-aligned bounding boxes are represented by its upper-left corner
* coordinate (x1,y1) and lower-right corner coordinate (x2,y2). A valid
@ -2597,25 +2664,34 @@ enum OperationType : int32_t {
* Inputs:
* * 0: A 2-D Tensor of shape [num_rois, num_classes], specifying the score
* of each bounding box proposal. The boxes are grouped by batches in the
* first dimension.
* first dimension. Zero num_rois is supported for this tensor.
* * 1: A 2-D Tensor specifying the bounding boxes of shape
* [num_rois, num_classes * 4], organized in the order [x1, y1, x2, y2].
* The boxes are grouped by batches in the first dimension. The sequential
* order of the boxes corresponds with input0. For input0 of type
* {@link OperandType::TENSOR_QUANT8_ASYMM}, this tensor should be of
* {@link OperandType::TENSOR_QUANT16_ASYMM}, with zeroPoint of 0 and
* scale of 0.125.
* scale of 0.125. Zero num_rois is supported for this tensor.
* * 2: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
* [num_rois], specifying the batch index of each box. Boxes with
* the same batch index are grouped together.
* * 3: An {@link OperandType::FLOAT32} scalar, score_threshold. Boxes
* with scores lower than the threshold are filtered before sending
* to the NMS algorithm.
* * 4: An {@link OperandType::FLOAT32} scalar, specifying the IoU
* threshold.
* * 5: An {@link OperandType::INT32} scalar, specifying the maximum
* * 4: An {@link OperandType::INT32} scalar, specifying the maximum
* number of selected bounding boxes for each image. Set to a negative
* value for unlimited number of output bounding boxes.
* * 5: An {@link OperandType::INT32} scalar, specifying the NMS
* kernel method, options are 0:hard, 1:linear, 2:gaussian.
* * 6: An {@link OperandType::FLOAT32} scalar, specifying the IoU
* threshold in hard and linear NMS kernel. This field is ignored if
* gaussian kernel is selected.
* * 7: An {@link OperandType::FLOAT32} scalar, specifying the sigma in
* gaussian NMS kernel. This field is ignored if gaussian kernel is
* not selected.
* * 8: An {@link OperandType::FLOAT32} scalar, nms_score_threshold.
* Boxes with scores lower than the threshold are dropped during the
* score updating phase in soft NMS.
*
* Outputs:
* * 0: A 1-D Tensor of the same {@link OperandType} as input0, with shape
@ -2633,8 +2709,8 @@ enum OperationType : int32_t {
* [num_output_rois], specifying the class of each output box. The
* sequential order of the boxes corresponds with output0.
* * 3: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
* [num_rois], specifying the batch index of each box. Boxes with
* the same batch index are grouped together.
* [num_output_rois], specifying the batch index of each box. Boxes
* with the same batch index are grouped together.
*
* Available since API level 29.
*/
@ -2970,8 +3046,8 @@ enum OperationType : int32_t {
* For type of {@link OperandType::TENSOR_QUANT16_ASYMM}, the
* scale must be 0.125 and the zero point must be 0.
* * 2: A 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
* [num_rois], specifying the batch index of each box. Boxes with
* the same batch index are grouped together.
* [num_output_rois], specifying the batch index of each box. Boxes
* with the same batch index are grouped together.
*
* Available since API level 29.
*/
@ -3637,7 +3713,7 @@ enum OperationType : int32_t {
* Supported tensor rank: from 1
*
* Inputs:
* * 0: A tensor.
* * 0: A tensor, may be zero-sized.
*
* Outputs:
* * 0: The output tensor of same shape as input0, but with
@ -3969,10 +4045,12 @@ enum OperationType : int32_t {
* the regions of interest, each line with format [x1, y1, x2, y2].
* For input0 of type {@link OperandType::TENSOR_QUANT8_ASYMM},
* this tensor should be of {@link OperandType::TENSOR_QUANT16_ASYMM},
* with zeroPoint of 0 and scale of 0.125.
* with zeroPoint of 0 and scale of 0.125. Zero num_rois is
* supported for this tensor.
* * 2: An 1-D {@link OperandType::TENSOR_INT32} tensor, of shape
* [num_rois], specifying the batch index of each box. Boxes with
* the same batch index are grouped together.
* the same batch index are grouped together. Zero num_rois is
* supported for this tensor.
* * 3: An {@link OperandType::INT32} scalar, specifying the output
* height of the output tensor.
* * 4: An {@link OperandType::INT32} scalar, specifying the output
@ -4137,7 +4215,7 @@ enum OperationType : int32_t {
* Supported tensor rank: from 1
*
* Inputs:
* * 0: An n-D tensor to take slice from.
* * 0: An n-D tensor to take slice from, may be zero-sized.
* * 1: A 1-D tensor of type {@link OperandType::TENSOR_INT32} specifying
* the beginning indices of the slice in each dimension.
* * 2: A 1-D tensor of type {@link OperandType::TENSOR_INT32} specifying
@ -4551,9 +4629,11 @@ enum OperationType : int32_t {
* [batch, height, width, channels]. Alternatively, the data layout could
* be NCHW, the data storage order of: [batch, channels, height, width].
*
* Inputs:
* Both resizing by shape and resizing by scale are supported.
*
* Inputs (resizing by shape):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input.
* the input. Zero batches is supported for this tensor.
* * 1: An {@link OperandType::INT32} scalar, specifying the output
* height of the output tensor.
* * 2: An {@link OperandType::INT32} scalar, specifying the output
@ -4561,6 +4641,24 @@ enum OperationType : int32_t {
* * 3: An {@link OperandType::BOOL} scalar, default to false.
* Set to true to specify NCHW data layout for input0 and output0.
*
* Inputs (resizing by scale):
* * 0: A 4-D tensor, of shape [batches, height, width, depth], specifying
* the input. Zero batches is supported for this tensor.
* * 1: A scalar, specifying height_scale, the scaling factor of the height
* dimension from the input tensor to the output tensor. The output
* height is calculated as new_height = floor(height * height_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
* * 2: A scalar, specifying width_scale, the scaling factor of the width
* dimension from the input tensor to the output tensor. The output
* width is calculated as new_width = floor(width * width_scale).
* The scalar must be of {@link OperandType::FLOAT16} if input0 is
* of {@link OperandType::TENSOR_FLOAT16} and of
* {@link OperandType::FLOAT32} otherwise.
* * 3: An {@link OperandType::BOOL} scalar, default to false.
* Set to true to specify NCHW data layout for input0 and output0.
*
* Outputs:
* * 0: The output 4-D tensor, of shape
* [batches, new_height, new_width, depth].