commit c95ca1b9d2012c4664641b93880300fc48827f8d
author Steven Moreland <smoreland@google.com> Wed Apr 17 17:24:29 2019 +0000
committer Gerrit Code Review <noreply-gerritcodereview@google.com> Wed Apr 17 17:24:29 2019 +0000
tree 22a514fe304eccb3a2c0d35ec14c9210facca683
parent ee4ee60689703adc8778beb105efc61033142262
parent 154fc1fabba13f97168644e6d154e773ca33ad2f

Merge "Remove bluetooth.a2dp from matrix as deprecated HAL"

current.txt

diff --git a/current.txt b/current.txt
index cdd6f68..c7e1866 100644
--- a/current.txt
+++ b/current.txt
@@ -451,7 +451,7 @@
 92714960d1a53fc2ec557302b41c7cc93d2636d8364a44bd0f85be0c92927ff8 android.hardware.neuralnetworks@1.2::IExecutionCallback
 36e1064c869965dee533c537cefbe87e54db8bd8cd45be7e0e93e00e8a43863a android.hardware.neuralnetworks@1.2::IPreparedModel
 e1c734d1545e1a4ae749ff1dd9704a8e594c59aea7c8363159dc258e93e0df3b android.hardware.neuralnetworks@1.2::IPreparedModelCallback
-209a5ee694b94328afb2af2768f1fe6a69148e2cbb85ec3c340a36eed818c697 android.hardware.neuralnetworks@1.2::types
+b75126d572c1788682a679ab53c2dbdf3fcd75f754b1370dbf09aaad0e19d397 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

neuralnetworks/1.2/types.hal

diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal
index 8c57796..839114f 100644
--- a/neuralnetworks/1.2/types.hal
+++ b/neuralnetworks/1.2/types.hal
@@ -1188,8 +1188,11 @@
      *   value if the recurrent projection layer exists, and should otherwise
      *   have no value.
      * * (API level >= 29) The four layer normalization weights either all have
-     *   values or none of them have values. Layer normalization is used when
-     *   values are present.
+     *   values or none of them have values. Additionally, if CIFG is used,
+     *   input layer normalization weights tensor is omitted and the other layer
+     *   normalization weights either all have values or none of them have
+     *   values. Layer normalization is used when the values of all the layer
+     *   normalization weights are present.
      *
      * References:
      *
@@ -3513,7 +3516,7 @@
      *      with input0.
      *
      * Outputs:
-     * * 0: The sum, a tensor of the same {@link OperandType} as input0.
+     * * 0: A tensor of the same {@link OperandType} as input0.
      *
      * Available since API level 29.
      */
@@ -3534,7 +3537,7 @@
      *      with input0.
      *
      * Outputs:
-     * * 0: The sum, a tensor of the same {@link OperandType} as input0.
+     * * 0: A tensor of the same {@link OperandType} as input0.
      *
      * Available since API level 29.
      */

neuralnetworks/1.2/vts/functional/ValidateModel.cpp

diff --git a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
index dc452e9..acf3cb6 100644
--- a/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
+++ b/neuralnetworks/1.2/vts/functional/ValidateModel.cpp
@@ -508,14 +508,15 @@
                 }
             }
         }
-        // BIDIRECTIONAL_SEQUENCE_RNN can have either on or two outputs
-        // depending on a mergeOutputs parameter
-        if (operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_RNN) {
-            for (const size_t outOprand : operation.outputs) {
-                if (operand == outOprand) {
-                    return true;
-                }
+        // BIDIRECTIONAL_SEQUENCE_LSTM and BIDIRECTIONAL_SEQUENCE_RNN can have
+        // either one or two outputs depending on their mergeOutputs parameter.
+        if (operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_LSTM ||
+            operation.type == OperationType::BIDIRECTIONAL_SEQUENCE_RNN) {
+          for (const size_t outOprand : operation.outputs) {
+            if (operand == outOprand) {
+              return true;
             }
+          }
         }
     }
     return false;