This is needed to be able to test DEQUANTIZE after adding
TENSOR_QUANT8_SYMM support.
Test: NeuralNetworksTest_static
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: Iba9b286df70919d7b67cd77c91e625a044bd686c
Merged-In: Iba9b286df70919d7b67cd77c91e625a044bd686c
(cherry picked from commit bf26a9e3d7)
This is needed to be able to test DEQUANTIZE after adding
TENSOR_QUANT8_SYMM support.
Test: NeuralNetworksTest_static
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: Iba9b286df70919d7b67cd77c91e625a044bd686c
This CL creates a new suite of tests to enable presubmit tests:
* PresubmitHalNeuralnetworksV1_0TargetTest
* PresubmitHalNeuralnetworksV1_1TargetTest
* PresubmitHalNeuralnetworksV1_2TargetTest
These tests are the same as the VTS tests, with the exception that they
will skip running all tests (but still pass) if the service cannot be
found and its name starts with "service-".
This change does not affect the existing NNAPI VTS tests.
Test: mma
Test: atest
Bug: 124040554
Change-Id: I36a38b66b21fd51d0ca381bb4e05a39266dd353f
(cherry picked from commit ed68233697)
Argument-dependent lookup will only work for operator>> if the operator
is in one of the argument's namespaces. This caused the enumerations to
pretty-print for V1_0, but not for V1_1 or V1_2. This change ensures the
V1_0 namespace is used.
Test: mma
Test: atest VtsHalNeuralnetworksV1_0TargetTest (verified the test output "OFFLINE" for DeviceStatus and "DEVICE_UNAVAILABLE" for ErrorStatus instead of raw byte value representation)
Test: atest VtsHalNeuralnetworksV1_1TargetTest (verified the test output "OFFLINE" for DeviceStatus and "DEVICE_UNAVAILABLE" for ErrorStatus instead of raw byte value representation)
Test: atest VtsHalNeuralnetworksV1_2TargetTest (verified ran and passed tests)
Fixes: 124316129
Change-Id: I764a46e2d87615b1f3da0ab0e6edb134bb533887
(cherry picked from commit 42a35bee10)
This CL creates a new suite of tests to enable presubmit tests:
* PresubmitHalNeuralnetworksV1_0TargetTest
* PresubmitHalNeuralnetworksV1_1TargetTest
* PresubmitHalNeuralnetworksV1_2TargetTest
These tests are the same as the VTS tests, with the exception that they
will skip running all tests (but still pass) if the service cannot be
found and its name starts with "service-".
This change does not affect the existing NNAPI VTS tests.
Test: mma
Test: atest
Bug: 124040554
Change-Id: I36a38b66b21fd51d0ca381bb4e05a39266dd353f
Argument-dependent lookup will only work for operator>> if the operator
is in one of the argument's namespaces. This caused the enumerations to
pretty-print for V1_0, but not for V1_1 or V1_2. This change ensures the
V1_0 namespace is used.
Test: mma
Test: atest VtsHalNeuralnetworksV1_0TargetTest (verified the test output "OFFLINE" for DeviceStatus and "DEVICE_UNAVAILABLE" for ErrorStatus instead of raw byte value representation)
Test: atest VtsHalNeuralnetworksV1_1TargetTest (verified the test output "OFFLINE" for DeviceStatus and "DEVICE_UNAVAILABLE" for ErrorStatus instead of raw byte value representation)
Test: atest VtsHalNeuralnetworksV1_2TargetTest (verified ran and passed tests)
Fixes: 124316129
Change-Id: I764a46e2d87615b1f3da0ab0e6edb134bb533887
The tmp directory is only removed when the driver reports caching not
supported, otherwise it is kept for debugging purpose.
Test: 1.2 VTS tests with sample driver
Change-Id: I5969beb1ec365c992765f40d7693630606f16e18
Merged-In: I5969beb1ec365c992765f40d7693630606f16e18
(cherry picked from commit 350d91b1df)
Test was failing with segmentation fault (and crashing whole VTS) when
device was not available.
Change-Id: Id0f28d061dc5858fa00ef1bac5f7aa467d860864
Merged-In: Id0f28d061dc5858fa00ef1bac5f7aa467d860864
(cherry picked from commit 70d25b813e)
The tmp directory is only removed when the driver reports caching not
supported, otherwise it is kept for debugging purpose.
Test: 1.2 VTS tests with sample driver
Change-Id: I5969beb1ec365c992765f40d7693630606f16e18
* Adds a specification of invalid scale and zero point for TENSOR_BOOL8.
This fixes vts failures for comparison ops.
* Removes (FUNDAMENTAL_MIN - 1) from invalid OperationTypes.
FUNDAMENTAL_MIN is equal to 0 and resulting -1 was statically casted to
uint32_t and passed 4294967295 as an invalid OperationType. However, our
validateOperation function interpreted this ID as an extension ID and
didn't fail.
* Adds mutateOperationOperandTypeSkip for QUANTIZE and DEQUANTIZE.
* Adds removeOperandSkip for BIDIRECTIONAL_SEQUENCE_RNN.
Fix: 121130841
Fix: 123247345
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Change-Id: Iefb502c6b9301d5470eb4cdaa46d398f1a0e512a
Merged-In: Iefb502c6b9301d5470eb4cdaa46d398f1a0e512a
(cherry picked from commit 923b8c5842)
This is a follow-up to change Ia9b99015eec7a48bbf969cbe503862271f09adca
Bug: 118605927
Test: mma
Change-Id: I7ddafca04bce6fd37a9c0877270cee325111d833
Merged-In: I7ddafca04bce6fd37a9c0877270cee325111d833
(cherry picked from commit 1ffe69a8e9)
Add the following tests for compilation caching:
- validation tests
- Test isCachingSupported
- Test prepareModelFromCache with invalid numFd and invalid access mode
- Test saveToCache with invalid numFd, invalid access mode,
invalid file size, and invalid fd offset
- execution test
- Save a mobilenet model to cache and then retrieve and run accuracy
evaluation.
- The same test but the file offsets for prepareModelFromCache is not at zero.
- security test
- CompilationCachingSecurityTest.CorruptedSecuritySensitiveCache
Randomly flip one bit of security-sensitive cache.
- CompilationCachingSecurityTest.WrongLengthSecuritySensitiveCache
Randomly append bytes to security-sensitive cache.
- CompilationCachingSecurityTest.WrongToken
Randomly flip one bit of cache token.
Bug: 119616526
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Test: VtsHalNeuralnetworksV1_xTargetTest with a test driver that can
read and write cache entries
Change-Id: Iae9211cb28ce972b29572dfedd45d1ade4dfdaf5
Merged-In: Iae9211cb28ce972b29572dfedd45d1ade4dfdaf5
(cherry picked from commit 3405878e5e)
Machine Learning is a fast moving domain: new operations and data types
are introduced at a staggering speed. The Android API, on the other
hand, evolves on a yearly cycle. Many application developers, OEMs, and
SoC vendors would like to be able to define new operations at a faster
cycle.
In OC-MR1, NNAPI provided a simple mechanism to mitigate this problem:
two OEM data types and an OEM operation. The downside of this mechanism is that
it is simplistic: There’s no guarantee of consistency between vendors.
Examples of features that are required by the first parties' use cases
that we would like to be able to define outside of the normal Android
release cycle:
- New data types:
- Sparse tensor (used by some speech generation models).
- 16 bit int tensor (needed by OCR).
- 16 bit float tensor.
- New operations:
- 16 bit quantized LSTM (needed by OCR).
- Basic primitives like sqrt and floor.
- Logical operations.
- Complex neural network layers.
- Control flow.
- Enhancement to existing operations:
- Concatenate supporting different scales/zeroPoints for arguments.
- High-dimensional tensors.
- Ordering of dimensions.
We are going to provide support for two types of extensions:
- NNAPI Platform extension. This is functionality that will become part of
future releases of NNAPI. These extensions provide generic,
non-vendor-specific functionality. Only the Android team can define new
platform extensions. These extensions will be defined in the master
branch of AOSP. Each extension comes with:
- Documentation defining the extension,
- A header file for the new constants,
- A parameter validation library to be used by drivers, and
- Validation tests akin to the CTS and VTS tests.
- Vendor extension. A vendor-specific extension is an alternative to OEM
operation and data types. Its usage will be limited only to first party apps
preinstalled on the /vendor or /odm partition.
Each vendor will be identified by a specific value to
prevent collisions between multiple IPs found on the same SoC. This
effectively creates a vendor-specific namespace. These identifiers are
assigned by Google.
This change only defines the new interface. The implementation follows
in changes Ie4e2530e4c81fabe4eb59b7a6ba4a3b4bb483bd1,
I02aa12f4a8444012ddf3b20c2bfbba6a21ce9ce9, and
Icf59ed04e602aa7a730eb1eb45e5f6b1204fafb3.
Bug: 118605927
Test: mma
Change-Id: Ia9b99015eec7a48bbf969cbe503862271f09adca
Merged-In: Ia9b99015eec7a48bbf969cbe503862271f09adca
(cherry picked from commit 9212018558)
* Adds a specification of invalid scale and zero point for TENSOR_BOOL8.
This fixes vts failures for comparison ops.
* Removes (FUNDAMENTAL_MIN - 1) from invalid OperationTypes.
FUNDAMENTAL_MIN is equal to 0 and resulting -1 was statically casted to
uint32_t and passed 4294967295 as an invalid OperationType. However, our
validateOperation function interpreted this ID as an extension ID and
didn't fail.
* Adds mutateOperationOperandTypeSkip for QUANTIZE and DEQUANTIZE.
* Adds removeOperandSkip for BIDIRECTIONAL_SEQUENCE_RNN.
Fix: 121130841
Fix: 123247345
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Change-Id: Iefb502c6b9301d5470eb4cdaa46d398f1a0e512a
Test dynamic output shape with generated models when
- Dimensions of output operands are fully specified
- Dimensions of output operands are unspecified with sufficient buffer
- Dimensions of output operands are unspecified with insufficient buffer
Test: VTS on 1.2 sample driver
Change-Id: I4d26395ce443687ccbd47445b36e3356d70035cc
Merged-In: I4d26395ce443687ccbd47445b36e3356d70035cc
(cherry picked from commit 929fd21e06)
- Instead of reporting PASS for unsupported tests, use GTEST_SKIP to
skip the tests at runtime.
Bug: 113356629
Test: mm
Test: VTS tests on HVX driver
Change-Id: I6a870b61809e58490e66dd4ea36ddeb64fc68a07
Merged-In: I6a870b61809e58490e66dd4ea36ddeb64fc68a07
(cherry picked from commit bb685a4a97)
FastMessageQueue is a Treble-compliant data structure that enables fast
communication between two processes. The FMQ object itself is an atomic
circular buffer that is optionally synchronized with a futex. However,
FMQ has no notion of ownership or lifetime across processes, so it must
be paired with higher-level constructs to manage the lifetime and
ownership.
The NNAPI is introducing the notion of an "Execution Burst" object (or
more simply a "Burst" object), which is similar to an
ANeuralNetworksExecution, but is intended to be reused across multiple
executions and has lower IPC overheads. It achieves this low IPC
overhead by replacing HIDL HwBinder calls with FMQ messages.
Specifically, it replaces IPreparedModel::executeSynchronously's call
from the client into the service with fmq_sync<FmqRequestDatum> (an FMQ
channel used to pass a serialized Request object) and it replaces
the return from the service into the client with
fmq_sync<FmqResultDatum> (an FMQ channel used to return serialized
result status and OutputShapes information).
Each channel is a unidirectional flow of information with exactly one
producer and exactly one consumer. The channels are created by the NN
runtime and passed to the service via
IPreparedModel::configureExecutionBurst.
This CL tests the Burst in both the execution path and validation path
in the Vendor Test Suite (VTS) in neuralnetworks/1.*/vts/functional/.
The VTS binary--VtsHalNeuralnetworksV1_2TargetTest--can be built and run
as any previous version could.
Bug: 119570067
Test: mma
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: I3a36484eff9565c2d028c07c099804a0289f294a
Merged-In: I3a36484eff9565c2d028c07c099804a0289f294a
(cherry picked from commit 814d8372f3)
Add the following tests for compilation caching:
- validation tests
- Test isCachingSupported
- Test prepareModelFromCache with invalid numFd and invalid access mode
- Test saveToCache with invalid numFd, invalid access mode,
invalid file size, and invalid fd offset
- execution test
- Save a mobilenet model to cache and then retrieve and run accuracy
evaluation.
- The same test but the file offsets for prepareModelFromCache is not at zero.
- security test
- CompilationCachingSecurityTest.CorruptedSecuritySensitiveCache
Randomly flip one bit of security-sensitive cache.
- CompilationCachingSecurityTest.WrongLengthSecuritySensitiveCache
Randomly append bytes to security-sensitive cache.
- CompilationCachingSecurityTest.WrongToken
Randomly flip one bit of cache token.
Bug: 119616526
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Test: VtsHalNeuralnetworksV1_xTargetTest with a test driver that can
read and write cache entries
Change-Id: Iae9211cb28ce972b29572dfedd45d1ade4dfdaf5
Machine Learning is a fast moving domain: new operations and data types
are introduced at a staggering speed. The Android API, on the other
hand, evolves on a yearly cycle. Many application developers, OEMs, and
SoC vendors would like to be able to define new operations at a faster
cycle.
In OC-MR1, NNAPI provided a simple mechanism to mitigate this problem:
two OEM data types and an OEM operation. The downside of this mechanism is that
it is simplistic: There’s no guarantee of consistency between vendors.
Examples of features that are required by the first parties' use cases
that we would like to be able to define outside of the normal Android
release cycle:
- New data types:
- Sparse tensor (used by some speech generation models).
- 16 bit int tensor (needed by OCR).
- 16 bit float tensor.
- New operations:
- 16 bit quantized LSTM (needed by OCR).
- Basic primitives like sqrt and floor.
- Logical operations.
- Complex neural network layers.
- Control flow.
- Enhancement to existing operations:
- Concatenate supporting different scales/zeroPoints for arguments.
- High-dimensional tensors.
- Ordering of dimensions.
We are going to provide support for two types of extensions:
- NNAPI Platform extension. This is functionality that will become part of
future releases of NNAPI. These extensions provide generic,
non-vendor-specific functionality. Only the Android team can define new
platform extensions. These extensions will be defined in the master
branch of AOSP. Each extension comes with:
- Documentation defining the extension,
- A header file for the new constants,
- A parameter validation library to be used by drivers, and
- Validation tests akin to the CTS and VTS tests.
- Vendor extension. A vendor-specific extension is an alternative to OEM
operation and data types. Its usage will be limited only to first party apps
preinstalled on the /vendor or /odm partition.
Each vendor will be identified by a specific value to
prevent collisions between multiple IPs found on the same SoC. This
effectively creates a vendor-specific namespace. These identifiers are
assigned by Google.
This change only defines the new interface. The implementation follows
in changes Ie4e2530e4c81fabe4eb59b7a6ba4a3b4bb483bd1,
I02aa12f4a8444012ddf3b20c2bfbba6a21ce9ce9, and
Icf59ed04e602aa7a730eb1eb45e5f6b1204fafb3.
Bug: 118605927
Test: mma
Change-Id: Ia9b99015eec7a48bbf969cbe503862271f09adca
Test dynamic output shape with generated models when
- Dimensions of output operands are fully specified
- Dimensions of output operands are unspecified with sufficient buffer
- Dimensions of output operands are unspecified with insufficient buffer
Test: VTS on 1.2 sample driver
Change-Id: I4d26395ce443687ccbd47445b36e3356d70035cc
FastMessageQueue is a Treble-compliant data structure that enables fast
communication between two processes. The FMQ object itself is an atomic
circular buffer that is optionally synchronized with a futex. However,
FMQ has no notion of ownership or lifetime across processes, so it must
be paired with higher-level constructs to manage the lifetime and
ownership.
The NNAPI is introducing the notion of an "Execution Burst" object (or
more simply a "Burst" object), which is similar to an
ANeuralNetworksExecution, but is intended to be reused across multiple
executions and has lower IPC overheads. It achieves this low IPC
overhead by replacing HIDL HwBinder calls with FMQ messages.
Specifically, it replaces IPreparedModel::executeSynchronously's call
from the client into the service with fmq_sync<FmqRequestDatum> (an FMQ
channel used to pass a serialized Request object) and it replaces
the return from the service into the client with
fmq_sync<FmqResultDatum> (an FMQ channel used to return serialized
result status and OutputShapes information).
Each channel is a unidirectional flow of information with exactly one
producer and exactly one consumer. The channels are created by the NN
runtime and passed to the service via
IPreparedModel::configureExecutionBurst.
This CL tests the Burst in both the execution path and validation path
in the Vendor Test Suite (VTS) in neuralnetworks/1.*/vts/functional/.
The VTS binary--VtsHalNeuralnetworksV1_2TargetTest--can be built and run
as any previous version could.
Bug: 119570067
Test: mma
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: I3a36484eff9565c2d028c07c099804a0289f294a
Enable VTS unit test for dynamic output shape deduction.
Only test dynamic output shape for V1_2::IDevice with V1_2::Model.
Bug: 73506513
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Change-Id: I4134e1ec54a15554eb8533134897279651b57da3
Merged-In: I4134e1ec54a15554eb8533134897279651b57da3
(cherry picked from commit a316581b21)
FastMessageQueue is a Treble-compliant data structure that enables fast
communication between two processes. The FMQ object itself is an atomic
circular buffer that is optionally synchronized with a futex. However,
FMQ has no notion of ownership or lifetime across processes, so it must
be paired with higher-level constructs to manage the lifetime and
ownership.
The NNAPI is introducing the notion of an "Execution Burst" object (or
more simply a "Burst" object), which is similar to an
ANeuralNetworksExecution, but is intended to be reused across multiple
executions and has lower IPC overheads. It achieves this low IPC
overhead by replacing HIDL HwBinder calls with FMQ messages.
Specifically, it replaces IPreparedModel::executeSynchronously's call
from the client into the service with fmq_sync<FmqRequestDatum> (an FMQ
channel used to pass a serialized Request object) and it replaces
the return from the service into the client with
fmq_sync<FmqResultDatum> (an FMQ channel used to return serialized
result status and OutputShapes information).
Each channel is a unidirectional flow of information with exactly one
producer and exactly one consumer. The channels are created by the NN
runtime and passed to the service via
IPreparedModel::configureExecutionBurst.
This CL defines the FmqRequestDatum and FmqResultDatum types in
types.hal. IBurstContext.hal defines IBurstContext, a HIDL object used
by the service to manage the resources of a Burst. IBurstCallback.hal
defines IBurstCallback, a HIDL callback object that can be used to
retrieve the handle to a resource the service has either not yet seen or
has evicted from its cache. Finally, IPreparedModel.hal is extended with
IPreparedModel::configureExecutionBurst to create the burst object.
Bug: 119570067
Test: mma
Change-Id: I333da70201531b1396efc714d096c277e8e1d47b
Merged-In: I333da70201531b1396efc714d096c277e8e1d47b
(cherry picked from commit 7e91e24fe1)
FastMessageQueue is a Treble-compliant data structure that enables fast
communication between two processes. The FMQ object itself is an atomic
circular buffer that is optionally synchronized with a futex. However,
FMQ has no notion of ownership or lifetime across processes, so it must
be paired with higher-level constructs to manage the lifetime and
ownership.
The NNAPI is introducing the notion of an "Execution Burst" object (or
more simply a "Burst" object), which is similar to an
ANeuralNetworksExecution, but is intended to be reused across multiple
executions and has lower IPC overheads. It achieves this low IPC
overhead by replacing HIDL HwBinder calls with FMQ messages.
Specifically, it replaces IPreparedModel::executeSynchronously's call
from the client into the service with fmq_sync<FmqRequestDatum> (an FMQ
channel used to pass a serialized Request object) and it replaces
the return from the service into the client with
fmq_sync<FmqResultDatum> (an FMQ channel used to return serialized
result status and OutputShapes information).
Each channel is a unidirectional flow of information with exactly one
producer and exactly one consumer. The channels are created by the NN
runtime and passed to the service via
IPreparedModel::configureExecutionBurst.
This CL defines the FmqRequestDatum and FmqResultDatum types in
types.hal. IBurstContext.hal defines IBurstContext, a HIDL object used
by the service to manage the resources of a Burst. IBurstCallback.hal
defines IBurstCallback, a HIDL callback object that can be used to
retrieve the handle to a resource the service has either not yet seen or
has evicted from its cache. Finally, IPreparedModel.hal is extended with
IPreparedModel::configureExecutionBurst to create the burst object.
Bug: 119570067
Test: mma
Change-Id: I333da70201531b1396efc714d096c277e8e1d47b
Enable VTS unit test for dynamic output shape deduction.
Only test dynamic output shape for V1_2::IDevice with V1_2::Model.
Bug: 73506513
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Change-Id: I4134e1ec54a15554eb8533134897279651b57da3
Remove ROTATED_BBOX_TRANSFORM since it is no longer needed.
Add DETECTION_POSTPROCESS for SSD NMS postprocessing op.
Bug: 120983926
Test: NeuralNetworksTest_static
Change-Id: Id6b1021c8707734499feddddf0aac24a3fff90f8
Added ExtraParams union for extra Operand parameters.
It's a more sensible approach than adding more fields
to the Operand struct.
Bug: 119249581
Test: NeuralNetworksTest_static
Test: VtsHalNeuralnetworksV1_0TargetTest
Test: VtsHalNeuralnetworksV1_1TargetTest
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: I59731134cf0ea34cf9e10342686d331da9e9c3b3
Merged-In: I59731134cf0ea34cf9e10342686d331da9e9c3b3
(cherry picked from commit faa59b8a2c)
- Instead of reporting PASS for unsupported tests, use GTEST_SKIP to
skip the tests at runtime.
Bug: 113356629
Test: mm
Test: VTS tests on HVX driver
Change-Id: I6a870b61809e58490e66dd4ea36ddeb64fc68a07
Bug: 119274127
Test: all of the following, with the appropriate android.hardware.neuralnetworks@1.${X}::IDevice/sample-all
VtsHalNeuralnetworksV1_0TargetTest
VtsHalNeuralnetworksV1_0TargetTest
VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
VtsHalNeuralnetworksV1_1TargetTest
VtsHalNeuralnetworksV1_1TargetTest
VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
VtsHalNeuralnetworksV1_2TargetTest
VtsHalNeuralnetworksV1_2TargetTest
Change-Id: Iedfa485b4008d9cec3b81ff4c0ce3ebc0b83c823
(cherry picked from commit 49e41678f5)
Bug: 119274127
Test: all of the following, with the appropriate android.hardware.neuralnetworks@1.${X}::IDevice/sample-all
VtsHalNeuralnetworksV1_0TargetTest
VtsHalNeuralnetworksV1_0TargetTest
VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
VtsHalNeuralnetworksV1_1CompatV1_0TargetTest
VtsHalNeuralnetworksV1_1TargetTest
VtsHalNeuralnetworksV1_1TargetTest
VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
VtsHalNeuralnetworksV1_2CompatV1_0TargetTest
VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
VtsHalNeuralnetworksV1_2CompatV1_1TargetTest
VtsHalNeuralnetworksV1_2TargetTest
VtsHalNeuralnetworksV1_2TargetTest
Change-Id: Iedfa485b4008d9cec3b81ff4c0ce3ebc0b83c823
Moves comments for type range values into their enums to make it harder
to forget to update them.
Adds missing float16 types for ARGMAX/ARGMIN/CAST.
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: [ PASSED ] 2519 tests.
Change-Id: Ic7c3df8c8fbff45fe497f304b6b2c7a09e7dc5a6
Merged-In: Ic7c3df8c8fbff45fe497f304b6b2c7a09e7dc5a6
(cherry picked from commit bbdab2feee)
Create 1.2 version IPreparedModel, IPreparedModelCallback, and
IExecutionCallback.
Currently the new interfaces are created the same as 1.0 version,
but will have more methods introduced in later CLs.
Bug: 73506513
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Change-Id: Icf4d04c22f88e825d87562f1489377fdf6bf585d
Merged-In: Icf4d04c22f88e825d87562f1489377fdf6bf585d
(cherry picked from commit b5cb8f7632)
Create 1.2 version IPreparedModel, IPreparedModelCallback, and
IExecutionCallback.
Currently the new interfaces are created the same as 1.0 version,
but will have more methods introduced in later CLs.
Bug: 73506513
Test: VtsHalNeuralnetworksV1_xTargetTest with 1.2 sample driver
Change-Id: Icf4d04c22f88e825d87562f1489377fdf6bf585d
Added ExtraParams union for extra Operand parameters.
It's a more sensible approach than adding more fields
to the Operand struct.
Bug: 119249581
Test: NeuralNetworksTest_static
Test: VtsHalNeuralnetworksV1_0TargetTest
Test: VtsHalNeuralnetworksV1_1TargetTest
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: I59731134cf0ea34cf9e10342686d331da9e9c3b3
* changes:
Replace TENSOR_QUANT16_ASYMM with TENSOR_QUANT16_SYMM
Fix VTS ValidationTest for 1.2 ops.
Adds float16 support to generated tests.
Autogenerates VTS ValidationTest tests.
Fix VTS ValidationTest for 1.2 ops.
Separates VTS tests by HAL version.
Moves comments for type range values into their enums to make it harder
to forget to update them.
Adds missing float16 types for ARGMAX/ARGMIN/CAST.
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: [ PASSED ] 2519 tests.
Change-Id: Ic7c3df8c8fbff45fe497f304b6b2c7a09e7dc5a6
This removes the use of a separately updated list of models
that has fallen out of sync.
Bug: 119293899
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_2CompatV1_1TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_2CompatV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_1TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.1::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_1CompatV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.1::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.0::IDevice/sample-all
Change-Id: I2d8804d78331b8fceab4c622c871802aa0f0a4b4
Merged-In: I2d8804d78331b8fceab4c622c871802aa0f0a4b4
(cherry picked from commit b5fe58b95a)
* Update doc string
* Update zero point mutation to check for symmetric quantization
Fix: 118671831
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: Id1999c793c839b892cfe45cbb245611b12db2a72
This abstracts the boundary values for OperandType and
OperationType to avoid the need to update them in the
model validation functions.
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_2CompatV1_1TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_2CompatV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Change-Id: I39155148d67215e32b4eb1991b885f65d5eeaca8
Merged-In: I39155148d67215e32b4eb1991b885f65d5eeaca8
(cherry-pick from c785d46eb6)
This abstracts the boundary values for OperandType and
OperationType to avoid the need to update them in the
model validation functions.
Test: VtsHalNeuralnetworksV1_2TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_2CompatV1_1TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Test: VtsHalNeuralnetworksV1_2CompatV1_0TargetTest --hal_service_instance=android.hardware.neuralnetworks@1.2::IDevice/sample-all
Change-Id: I39155148d67215e32b4eb1991b885f65d5eeaca8
This makes it easier to find all the places that need to be changed
after adding a new type to MixedTyped.
Test: VtsHalNeuralnetworksV1_2TargetTest
Change-Id: I92867de6574ec6dc1a17e30d889c79501ea93063
Merged-In: I92867de6574ec6dc1a17e30d889c79501ea93063
(cherry picked from commit 9b490f4833)
