Performs element wise multiplications on element values in the input tensor data with a scale.
Pixelwise multiplication is performed between the pixel values in two tensors and a scalar floatingpoint number scale. The scale with a value of \( {1}/{2^n} \), where n is an integer and \( 0 \le n \le 15 \), and 1/255 (0x1.010102p8 C99 float hex) must be supported. The support for other values of scale is not prohibited. Furthermore, for scale with a value of 1/255 the rounding policy of VX_ROUND_POLICY_TO_NEAREST_EVEN
must be supported whereas for the scale with value of \( {1}/{2^n} \) the rounding policy of VX_ROUND_POLICY_TO_ZERO
must be supported. The support of other rounding modes for any values of scale is not prohibited.

vx_node VX_API_CALL  vxTensorMultiplyNode (vx_graph graph, vx_tensor input1, vx_tensor input2, vx_scalar scale, vx_enum overflow_policy, vx_enum rounding_policy, vx_tensor output) 
 [Graph] Performs element wise multiplications on element values in the input tensor data with a scale. More...


vx_status VX_API_CALL  vxuTensorMultiply (vx_context context, vx_tensor input1, vx_tensor input2, vx_scalar scale, vx_enum overflow_policy, vx_enum rounding_policy, vx_tensor output) 
 [Immediate] Performs element wise multiplications on element values in the input tensor data with a scale. More...


[Graph] Performs element wise multiplications on element values in the input tensor data with a scale.
 Parameters

[in]  graph  The handle to the graph. 
[in]  input1  Input tensor data. Implementations must support input tensor data type VX_TYPE_INT16 with fixed_point_position 8, and tensor data types VX_TYPE_UINT8 and VX_TYPE_INT8 , with fixed_point_position 0. 
[in]  input2  Input tensor data. The dimensions and sizes of input2 match those of input1, unless the vx_tensor of one or more dimensions in input2 is 1. In this case, those dimensions are treated as if this tensor was expanded to match the size of the corresponding dimension of input1, and data was duplicated on all terms in that dimension. After this expansion, the dimensions will be equal. The data type must match the data type of Input1. 
[in]  scale  A nonnegative VX_TYPE_FLOAT32 multiplied to each product before overflow handling. 
[in]  overflow_policy  A vx_convert_policy_e enumeration. 
[in]  rounding_policy  A vx_round_policy_e enumeration. 
[out]  output  The output tensor data with the same dimensions as the input tensor data. 
 Returns
vx_node
.

A node reference
vx_node
. Any possible errors preventing a successful creation should be checked using vxGetStatus
.
[Immediate] Performs element wise multiplications on element values in the input tensor data with a scale.
 Parameters

[in]  context  The reference to the overall context. 
[in]  input1  Input tensor data. Implementations must support input tensor data type VX_TYPE_INT16 with fixed_point_position 8, and tensor data types VX_TYPE_UINT8 and VX_TYPE_INT8 , with fixed_point_position 0. 
[in]  input2  Input tensor data. The dimensions and sizes of input2 match those of input1, unless the vx_tensor of one or more dimensions in input2 is 1. In this case, those dimensions are treated as if this tensor was expanded to match the size of the corresponding dimension of input1, and data was duplicated on all terms in that dimension. After this expansion, the dimensions will be equal. The data type must match the data type of Input1. 
[in]  scale  A nonnegative VX_TYPE_FLOAT32 multiplied to each product before overflow handling. 
[in]  overflow_policy  A vx_convert_policy_e enumeration. 
[in]  rounding_policy  A vx_round_policy_e enumeration. 
[out]  output  The output tensor data with the same dimensions as the input tensor data. 
 Returns
 A
vx_status_e
enumeration.
 Return values
