diff --git a/current.txt b/current.txt
index 4f1e86b..978f6c6 100644
--- a/current.txt
+++ b/current.txt
@@ -383,6 +383,5 @@
 
 # ABI preserving changes to HALs during Android Q
 574e8f1499436fb4075894dcae0b36682427956ecb114f17f1fe22d116a83c6b android.hardware.neuralnetworks@1.0::IPreparedModel
-b07802a3433a9abec67a41525dc04eab9efb62760414e1d37e2f72cc5ae9cb8a android.hardware.neuralnetworks@1.0::types
-bf18f51bfee84461f9831f3754f5c68ce2b29e42fe9d59ef8a33163e77f8edbf android.hardware.neuralnetworks@1.1::types
-
+1a5ae9793223658174258b523763c557abad6fb917df0b8e3cc097fc89035811 android.hardware.neuralnetworks@1.0::types
+4310eb8272f085914952f3bfb73a8f8bb477a80e8b93596f0ea5acb58546b66d android.hardware.neuralnetworks@1.1::types
diff --git a/neuralnetworks/1.0/types.hal b/neuralnetworks/1.0/types.hal
index 5a40e4e..887fdf1 100644
--- a/neuralnetworks/1.0/types.hal
+++ b/neuralnetworks/1.0/types.hal
@@ -596,8 +596,8 @@
      * * 0: A 4-D tensor, of shape [batches, height, width, depth].
      *
      * Outputs:
-     * * 0: The output 4-D tensor, of shape
-     *      [batches, out_height, out_width, depth].
+     * * 0: The output 4-D tensor, of the same shape as input
+     *      [batches, height, width, depth].
      */
     L2_NORMALIZATION = 11,
 
@@ -1282,8 +1282,8 @@
      *      input height and width.
      *
      * Outputs:
-     * * 0: The output 4-D tensor, of shape [batch, height/block_size,
-     *      width/block_size, depth*block_size*block_size].
+     * * 0: The output 4-D tensor, of shape [batches, height/block_size,
+     *      width/block_size, depth_in*block_size*block_size].
      */
     SPACE_TO_DEPTH = 26,
 
@@ -1410,28 +1410,36 @@
 enum OperandLifeTime : int32_t {
     /**
      * The operand is internal to the model. It's created by an operation and
-     * consumed by other operations.
+     * consumed by other operations. It must be an output operand of
+     * exactly one operation.
      */
     TEMPORARY_VARIABLE,
 
     /**
-     * The operand is an input of the model. An operand can't be both
-     * input and output of a model.
+     * The operand is an input of the model. It must not be an output
+     * operand of any operation.
+     *
+     * An operand can't be both input and output of a model.
      */
     MODEL_INPUT,
 
     /**
-     * The operand is an output of the model.
+     * The operand is an output of the model. It must be an output
+     * operand of exactly one operation.
+     *
+     * An operand can't be both input and output of a model.
      */
     MODEL_OUTPUT,
 
     /**
-     * The operand is a constant found in Model.operandValues.
+     * The operand is a constant found in Model.operandValues. It must
+     * not be an output operand of any operation.
      */
     CONSTANT_COPY,
 
     /**
-     * The operand is a constant that was specified via a Memory object.
+     * The operand is a constant that was specified via a Memory
+     * object. It must not be an output operand of any operation.
      */
     CONSTANT_REFERENCE,
 
@@ -1641,19 +1649,21 @@
     /**
      * All operations included in the model.
      *
-     * The operations are sorted into execution order.
+     * The operations are sorted into execution order. Every operand
+     * with lifetime MODEL_OUTPUT or TEMPORARY_VARIABLE must be
+     * written before it is read.
      */
     vec<Operation> operations;
 
     /**
-     * Input indexes of the model.
+     * Input indexes of the model. There must be at least one.
      *
      * Each value corresponds to the index of the operand in "operands".
      */
     vec<uint32_t> inputIndexes;
 
     /**
-     * Output indexes of the model.
+     * Output indexes of the model. There must be at least one.
      *
      * Each value corresponds to the index of the operand in "operands".
      */
diff --git a/neuralnetworks/1.1/types.hal b/neuralnetworks/1.1/types.hal
index b5718f3..7b2a21a 100644
--- a/neuralnetworks/1.1/types.hal
+++ b/neuralnetworks/1.1/types.hal
@@ -137,13 +137,19 @@
      * * 1: A 2-D Tensor of {@link OperandType::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
+     *      padding[i, 0] specifies the number of elements to be padded in the
      *      front of dimension i.
-     *      padding[i, 1] specifies the number of element to be padded after the
+     *      padding[i, 1] specifies the number of elements to be padded after the
      *      end of dimension i.
      *
      * Outputs:
-     * * 0: A tensor of the same {@link OperandType} as input0.
+     * * 0: A tensor of the same {@link OperandType} as input0. The
+     *      output tensor has the same rank as input0, and each
+     *      dimension of the output tensor has the same size as the
+     *      corresponding dimension of the input tensor plus the size
+     *      of the padding:
+     *          output0.dimension[i] =
+     *              padding[i, 0] + input0.dimension[i] + padding[i, 1]
      */
     PAD = 32,
 
@@ -377,19 +383,21 @@
     /**
      * All operations included in the model.
      *
-     * The operations are sorted into execution order.
+     * The operations are sorted into execution order. Every operand
+     * with lifetime MODEL_OUTPUT or TEMPORARY_VARIABLE must be
+     * written before it is read.
      */
     vec<Operation> operations;
 
     /**
-     * Input indexes of the model.
+     * Input indexes of the model. There must be at least one.
      *
      * Each value corresponds to the index of the operand in "operands".
      */
     vec<uint32_t> inputIndexes;
 
     /**
-     * Output indexes of the model.
+     * Output indexes of the model. There must be at least one.
      *
      * Each value corresponds to the index of the operand in "operands".
      */