diff --git a/current.txt b/current.txt index 575c699102..e2d14083cc 100644 --- a/current.txt +++ b/current.txt @@ -602,10 +602,11 @@ b69a7615c508acf5c5201efd1bfa3262167874fc3594e2db5a3ff93addd8ac75 android.hardwar eb2fa0c883c2185d514be0b84c179b283753ef0c1b77b45b4f359bd23bba8b75 android.hardware.neuralnetworks@1.0::IPreparedModel 92e101b30e47bdf526a01c52cecfbe730def5997b8260ab497eb949eb2a6dcdf android.hardware.neuralnetworks@1.0::types 5f6d3097ba84cb63c430787123f4de1b31c11f90b531b98eae9a8623a5ae962a android.hardware.neuralnetworks@1.1::types +c2711d8748ccbcc858d5d5ec1abf145d9ab4c0b27db8ca215d7c39665a9b6652 android.hardware.neuralnetworks@1.1::types # b/155508675, b/155662254, b/155238914 fb382e986c10b8fbb797a8546e8f9ea6d1107bfe6f3fb7e57f6bbbf1f807a906 android.hardware.neuralnetworks@1.2::IDevice 40e71cd693de5b832325c5d8f081f2ff20a7ba2b89d401cee5b4b3eb0e241681 android.hardware.neuralnetworks@1.2::IPreparedModel ee1a0dee5be00a6fe2d4d3270068c78016dcb194d768fe07ed894ea20904037f android.hardware.neuralnetworks@1.2::types -882b1c042ff842d7c52a794fab60bf6c599ef6b100ce99fa1772615096811d05 android.hardware.neuralnetworks@1.2::types # b/155508675 +9c53b727cfa9efde38ebe3914e1e95939cff29c072a1b8c8f419d24853b98831 android.hardware.neuralnetworks@1.2::types # b/155508675, b/155662254, b/155238914, b/155660285 a785a57447a81e9c130eef6904c3a5c256076c6a04588c40620ebd6fa2660d77 android.hardware.radio@1.2::types 1a6e2bd289f22931c526b21916910f1d4c436b7acb9556e4243de4ce8e6cc2e4 android.hardware.soundtrigger@2.0::ISoundTriggerHwCallback fd65298e1e09e0e3c781ab18305920d757dbe55a3b459ce17814ec5cf6dfee99 android.hardware.wifi@1.0::IWifiP2pIface @@ -719,7 +720,7 @@ a3eddd9bbdc87e8c22764070037dd1154f1cf006e6fba93364c4f85d4c134a19 android.hardwar ee9dc34b9925b8367b1111c72bd6d9d375432735e451572ca5a665d8516a7744 android.hardware.neuralnetworks@1.3::IPreparedModel eee3430cc86c97c7b407495863d8fb61da6f1a64b7721e77b9b4909b11b174e9 android.hardware.neuralnetworks@1.3::IPreparedModelCallback acf84925f8ee0a651f2ec547ac334034de266479b93af5434f6c1f25e66aba96 android.hardware.neuralnetworks@1.3::types -07801d19ca8a4f20543dae6b4d0c4d8b87e5161d3c431e973a1839cb7915a666 android.hardware.neuralnetworks@1.3::types # b/155508675 +e9080d04218e98512b63aace9ff3da52f0130238391f15cbbf7df396a3ec9072 android.hardware.neuralnetworks@1.3::types # b/155508675, b/155662254, b/155238914, b/155660285 b454df853441c12f6e425e8a60dd29fda20f5e6e39b93d1103e4b37495db38aa android.hardware.radio@1.5::IRadio fcbb0742a88215ee7a6d7ce0825d253eb2b50391fc6c8c48667f9fd7f6d4549e android.hardware.radio@1.5::IRadioIndication b809193970a91ca637a4b0184767315601d32e3ef3d5992ffbc7a8d14a14f015 android.hardware.radio@1.5::IRadioResponse diff --git a/neuralnetworks/1.1/types.hal b/neuralnetworks/1.1/types.hal index da7ba78734..c8cdd594dc 100644 --- a/neuralnetworks/1.1/types.hal +++ b/neuralnetworks/1.1/types.hal @@ -126,6 +126,8 @@ enum OperationType : @1.0::OperationType { * * 0: A tensor of the same {@link OperandType} as input0. * For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor, * the scale and zeroPoint must be the same as input0. + * If all dimensions are reduced and keep_dims is false, the output + * shape is [1]. */ MEAN = 31, @@ -232,6 +234,8 @@ enum OperationType : @1.0::OperationType { * removed. * For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor, * the scale and zeroPoint must be the same as input0. + * If all input dimensions are equal to 1 and are to be squeezed, the + * output shape is [1]. */ SQUEEZE = 34, @@ -278,6 +282,8 @@ enum OperationType : @1.0::OperationType { * where k is the number of bits set in shrink_axis_mask. * For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor, * the scale and zeroPoint must be the same as input0. + * If shrink_axis_mask is true for all input dimensions, the output + * shape is [1]. */ STRIDED_SLICE = 35, diff --git a/neuralnetworks/1.2/types.hal b/neuralnetworks/1.2/types.hal index 9eff7ff91a..92cf2aa5e4 100644 --- a/neuralnetworks/1.2/types.hal +++ b/neuralnetworks/1.2/types.hal @@ -1955,6 +1955,8 @@ enum OperationType : int32_t { * * 0: A tensor of the same {@link OperandType} as input0. * For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor, * the scale and zeroPoint must be the same as input0. + * If all dimensions are reduced and keep_dims is false, the output + * shape is [1]. */ MEAN = @1.1::OperationType:MEAN, @@ -2078,6 +2080,8 @@ enum OperationType : int32_t { * removed. * For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor, * the scale and zeroPoint must be the same as input0. + * If all input dimensions are equal to 1 and are to be squeezed, the + * output shape is [1]. */ SQUEEZE = @1.1::OperationType:SQUEEZE, @@ -2125,6 +2129,8 @@ enum OperationType : int32_t { * where k is the number of bits set in shrink_axis_mask. * For a {@link OperandType::TENSOR_QUANT8_ASYMM} tensor, * the scale and zeroPoint must be the same as input0. + * If shrink_axis_mask is true for all input dimensions, the output + * shape is [1]. */ STRIDED_SLICE = @1.1::OperationType:STRIDED_SLICE, @@ -2239,6 +2245,7 @@ enum OperationType : int32_t { * * Outputs: * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor. + * If input is 1-dimensional, the output shape is [1]. */ // There is no underscore in ARG_MAX to avoid name conflict with // the macro defined in libc/kernel/uapi/linux/limits.h. @@ -2263,6 +2270,7 @@ enum OperationType : int32_t { * * Outputs: * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor. + * If input is 1-dimensional, the output shape is [1]. */ ARGMIN = 40, // See ARGMAX for naming discussion. diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal index 83cf442e07..39ea4c24f2 100644 --- a/neuralnetworks/1.3/types.hal +++ b/neuralnetworks/1.3/types.hal @@ -2012,6 +2012,8 @@ enum OperationType : int32_t { * For a {@link OperandType::TENSOR_QUANT8_ASYMM} and * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor, * the scale and zeroPoint must be the same as input0. + * If all dimensions are reduced and keep_dims is false, the output + * shape is [1]. */ MEAN = @1.2::OperationType:MEAN, @@ -2141,6 +2143,8 @@ enum OperationType : int32_t { * For a {@link OperandType::TENSOR_QUANT8_ASYMM} and * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor, * the scale and zeroPoint must be the same as input0. + * If all input dimensions are equal to 1 and are to be squeezed, the + * output shape is [1]. */ SQUEEZE = @1.2::OperationType:SQUEEZE, @@ -2190,6 +2194,8 @@ enum OperationType : int32_t { * For a {@link OperandType::TENSOR_QUANT8_ASYMM} and * {@link OperandType::TENSOR_QUANT8_ASYMM_SIGNED} tensor, * the scale and zeroPoint must be the same as input0. + * If shrink_axis_mask is true for all input dimensions, the output + * shape is [1]. */ STRIDED_SLICE = @1.2::OperationType:STRIDED_SLICE, @@ -2313,6 +2319,7 @@ enum OperationType : int32_t { * * Outputs: * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor. + * If input is 1-dimensional, the output shape is [1]. */ // There is no underscore in ARG_MAX to avoid name conflict with // the macro defined in libc/kernel/uapi/linux/limits.h. @@ -2338,6 +2345,7 @@ enum OperationType : int32_t { * * Outputs: * * 0: An (n - 1)-D {@link OperandType::TENSOR_INT32} tensor. + * If input is 1-dimensional, the output shape is [1]. */ ARGMIN = @1.2::OperationType:ARGMIN, // See ARGMAX for naming discussion.