diff --git a/current.txt b/current.txt
index 8c2742b..e571692 100644
--- a/current.txt
+++ b/current.txt
@@ -655,7 +655,7 @@
 4167dc3ad35e9cd0d2057d4868c7675ae2c3c9d05bbd614c1f5dccfa5fd68797 android.hardware.neuralnetworks@1.3::IExecutionCallback
 7d23020248194abbee8091cc624f39a5a6d7ccba338b172d5d2d3df0cceffbee android.hardware.neuralnetworks@1.3::IPreparedModel
 0439a1fbbec7f16e5e4c653d85ac685d51bfafbae15b8f8cca530acdd7d6a8ce android.hardware.neuralnetworks@1.3::IPreparedModelCallback
-162515505235bc770601f02c3537f9ccf11582583bf7b11dd2ec81fab6855333 android.hardware.neuralnetworks@1.3::types
+26c643aedf4e28b8d82e517d9cd70601b37f881e1ea94f09808d9e233517e400 android.hardware.neuralnetworks@1.3::types
 3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
 c67aaf26a7a40d14ea61e70e20afacbd0bb906df1704d585ac8599fbb69dd44b android.hardware.wifi.hostapd@1.2::IHostapd
 11f6448d15336361180391c8ebcdfd2d7cf77b3782d577e594d583aadc9c2877 android.hardware.wifi.hostapd@1.2::types
diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal
index 0f51b1a..6a852d1 100644
--- a/neuralnetworks/1.3/types.hal
+++ b/neuralnetworks/1.3/types.hal
@@ -4987,6 +4987,56 @@
     WHILE = 97,
 
     /**
+     * Computes exponential linear activation on the input tensor element-wise.
+     *
+     * The output is calculated using the following formula:
+     *
+     *     ELU(x) = max(0, x) + min(0, alpha * (exp(x) - 1))
+     *
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input. May be zero-sized.
+     * * 1: A scalar, specifying the alpha parameter.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT16},
+     *      the alpha value must be of {@link OperandType::FLOAT16}.
+     *      For input tensor of {@link OperandType::TENSOR_FLOAT32},
+     *      the alpha value must be of {@link OperandType::FLOAT32}.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape and type as input0.
+     */
+    ELU = 98,
+
+    /**
+     * Computes hard-swish activation on the input tensor element-wise.
+     *
+     * Hard swish activation is introduced in
+     * https://arxiv.org/pdf/1905.02244.pdf
+     *
+     * The output is calculated using the following formula:
+     *
+     *     h-swish(x) = x * max(0, min(6, (x + 3))) / 6
+
+     * Supported tensor {@link OperandType}:
+     * * {@link OperandType::TENSOR_FLOAT16}
+     * * {@link OperandType::TENSOR_FLOAT32}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM}
+     * * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED}
+     *
+     * Inputs:
+     * * 0: A tensor, specifying the input. May be zero-sized.
+     *
+     * Outputs:
+     * * 0: The output tensor of same shape and type as input0.
+     *      Scale and zero point of this tensor may be different from the input
+     *      tensor's parameters.
+     */
+    HARD_SWISH = 99,
+
+    /**
      * DEPRECATED. Since NNAPI 1.2, extensions are the preferred alternative to
      * OEM operation and data types.
      *
@@ -5008,7 +5058,7 @@
 enum OperationTypeRange : uint32_t {
     BASE_MIN        = 0,
     FUNDAMENTAL_MIN = 0,
-    FUNDAMENTAL_MAX = 97,
+    FUNDAMENTAL_MAX = 99,
     OEM_MIN         = 10000,
     OEM_MAX         = 10000,
     BASE_MAX        = 0xFFFF,