Evolution-x/hardware_interfaces
1
0
Fork 0
mirror of https://github.com/Evolution-X/hardware_interfaces synced 2026-02-01 16:50:18 +00:00
Code Issues Packages Projects Releases Wiki Activity

Move OEM codes out of NeuralNetworks.h to new file NeuralNetworksOEM.h.

Browse Source 
Also remove FAKE_QUANT operation.

Bug: 63905942
Test: nn/runtime/tests, vts

Change-Id: Icfb5e7dbb9c2cca6e719ec2ab6344dbe5d95c86b
This commit is contained in:
David Gross
2017-09-13 12:31:33 -07:00
parent 7c353e9dd8
commit a7cdb30b19
1 changed files with 43 additions and 44 deletions
Download Patch File Download Diff File Expand all files Collapse all files

87
neuralnetworks/1.0/types.hal
View File

@@ -19,56 +19,55 @@
package android.hardware.neuralnetworks@1.0;
// The types an operand can have.
// These values are the same as found in the NeuralNetworks.h file.
// When modifying, be sure to update HAL_NUM_OPERAND_TYPES in HalIntefaces.h.
// These values are the same as found in the NeuralNetworks.h and NeuralNetworksOEM.h files.
enum OperandType : uint32_t {
OEM = 0,
FLOAT32 = 1,
INT32 = 2, // TODO: is this needed?
UINT32 = 3,
TENSOR_OEM_BYTE = 4,
TENSOR_FLOAT32 = 5,
TENSOR_INT32 = 6,
TENSOR_QUANT8_ASYMM = 7,
FLOAT32 = 0,
INT32 = 1,
UINT32 = 2,
TENSOR_FLOAT32 = 3,
TENSOR_INT32 = 4,
TENSOR_QUANT8_ASYMM = 5,
OEM = 10000,
TENSOR_OEM_BYTE = 10001,
};
// The type of operations. Unlike the operation types found in
// NeuralNetworks.h file, these specify the data type they operate on.
// The type of operations. Unlike the operation types found in the
// NeuralNetworks.h and NeuralNetworksOEM.h files, these specify the data type they operate on.
// This is done to simplify the work of drivers.
// TODO: Currently they are the same. Add a conversion when finalizing the model.
// When modifying, be sure to update HAL_NUM_OPERATION_TYPES in HalIntefaces.h.
enum OperationType : uint32_t {
OEM_OPERATION = 0,
ADD = 1,
AVERAGE_POOL_2D = 2,
CONCATENATION = 3,
CONV_2D = 4,
DEPTHWISE_CONV_2D = 5,
DEPTH_TO_SPACE = 6,
DEQUANTIZE = 7,
EMBEDDING_LOOKUP = 8,
FAKE_QUANT = 9,
FLOOR = 10,
FULLY_CONNECTED = 11,
HASHTABLE_LOOKUP = 12,
L2_NORMALIZATION = 13,
L2_POOL_2D = 14,
LOCAL_RESPONSE_NORMALIZATION = 15,
LOGISTIC = 16,
LSH_PROJECTION = 17,
LSTM = 18,
MAX_POOL_2D = 19,
MUL = 20,
RELU = 21,
RELU1 = 22,
RELU6 = 23,
RESHAPE = 24,
RESIZE_BILINEAR = 25,
RNN = 26,
SOFTMAX = 27,
SPACE_TO_DEPTH = 28,
SVDF = 29,
TANH = 30,
ADD = 0,
AVERAGE_POOL_2D = 1,
CONCATENATION = 2,
CONV_2D = 3,
DEPTHWISE_CONV_2D = 4,
DEPTH_TO_SPACE = 5,
DEQUANTIZE = 6,
EMBEDDING_LOOKUP = 7,
FLOOR = 8,
FULLY_CONNECTED = 9,
HASHTABLE_LOOKUP = 10,
L2_NORMALIZATION = 11,
L2_POOL_2D = 12,
LOCAL_RESPONSE_NORMALIZATION = 13,
LOGISTIC = 14,
LSH_PROJECTION = 15,
LSTM = 16,
MAX_POOL_2D = 17,
MUL = 18,
RELU = 19,
RELU1 = 20,
RELU6 = 21,
RESHAPE = 22,
RESIZE_BILINEAR = 23,
RNN = 24,
SOFTMAX = 25,
SPACE_TO_DEPTH = 26,
SVDF = 27,
TANH = 28,
OEM_OPERATION = 10000,
};
// Fused activation functions