diff --git a/current.txt b/current.txt
index 33d0c3c..69996dd 100644
--- a/current.txt
+++ b/current.txt
@@ -450,7 +450,7 @@
 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
diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 7691642..8c57796 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -187,6 +187,10 @@
      *     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 @@
      *
      * 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 @@
      *
      * 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 @@
      *            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 @@
      *
      * 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 @@
      *
      * 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 @@
      * 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 @@
      *      [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 @@
      * 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 @@
      *
      * 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 @@
      *
      * 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 @@
      *
      * 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 @@
      * 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 @@
      *
      * 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 @@
      *
      * 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 @@
      * * {@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 @@
      * 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 @@
      * 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 @@
      * 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 @@
      * [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 @@
      *      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 @@
      * 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 @@
      * 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 @@
      *     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 @@
      *     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 @@
      *
      * 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 @@
      * * 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 @@
      *      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 @@
     /**
      * 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 @@
      * 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 @@
      *      [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 @@
      *      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 @@
      * 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 @@
      *      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 @@
      * 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 @@
      * [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 @@
      * * 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].