Introduce LOGICAL_AND_EX in NeuralNetworksEx.h (#3563)

This patch Introduces LOGICAL_AND_EX in NeuralNetworksEx.h.
Related issue: #3459

Signed-off-by: prasannar <prasanna.r@samsung.com>

diff --git a/include/NeuralNetworksEx.h b/include/NeuralNetworksEx.h
index efc0abe..05699f5 100644 (file)
--- a/include/NeuralNetworksEx.h
+++ b/include/NeuralNetworksEx.h
@@ -329,6 +329,41 @@ typedef enum {
      *      A non-zero byte represents True. A zero indicates otherwise.
      */
     ANEURALNETWORKS_LOGICAL_NOT_EX = 50018,
+
+    /**
+     * Computes element-wise truth value of two input tensors for LOGICAL AND.
+     *
+     * Takes two input tensors of identical {@link OperandCode} and compatible dimensions.
+     * The output is the result of comparison of two input tensors.
+     *
+     * Two dimensions are compatible when:
+     *     1. they are equal, or
+     *     2. one of them is 1
+     *
+     * The size of the output is the maximum size along each dimension of the
+     * input operands. It starts with the trailing dimensions, and works its way
+     * forward.
+     *
+     * Supported tensor {@link OperandCode}:
+     * * {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM}
+     *
+     * Supported tensor rank: up to 4
+     *
+     * Inputs:
+     * * 0: An n-D boolean tensor, specifying the first input.
+     *      Stored as {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM} with offset 0
+     *      and scale 1.0f.
+     *      A non-zero byte represents True, a hit. A zero indicates otherwise.
+     * * 1: A tensor of the same {@link OperandCode}, and compatible dimensions
+     *      as input0.
+     *
+     * Outputs:
+     * * 0: A boolean tensor indicating the truth value of two input tensors for LOGICAL AND.
+     *      Stored as {@link ANEURALNETWORKS_TENSOR_QUANT8_ASYMM} with offset 0
+     *      and scale 1.0f.
+     *      A non-zero byte represents True, a hit. A zero indicates otherwise.
+     */
+    ANEURALNETWORKS_LOGICAL_AND_EX = 50019,
 } OperationCodeEx;  // extends OperationCode
 
 typedef OperationCodeEx ANeuralNetworksOperationTypeEx;