Merge changes from topic "nn_memory_domain_hal"
* changes:
Add memory domain VTS generated tests.
Memory Domain HAL: Define HAL APIs.
diff --git a/current.txt b/current.txt
index e7ee6bc..3dc3968 100644
--- a/current.txt
+++ b/current.txt
@@ -650,10 +650,11 @@
7a04ea5595ed418ca3e91c28b8bd7353dd988be9be7b0c8c9e64fb4b77bd4523 android.hardware.keymaster@4.1::types
df9c79c4fdde2821550c6d5c3d07f5ec0adfb1b702561ce543c906ddef698703 android.hardware.media.c2@1.1::IComponent
a3eddd9bbdc87e8c22764070037dd1154f1cf006e6fba93364c4f85d4c134a19 android.hardware.media.c2@1.1::IComponentStore
-9e59fffceed0dd72a9799e04505db5f777bbbea1af0695ba4107ef6d967c6fda android.hardware.neuralnetworks@1.3::IDevice
-258825966435b3ed08832055bb736d81516013e405f161d9ccde9a90cfcdde83 android.hardware.neuralnetworks@1.3::IPreparedModel
+4b5c8546533db9412fec6d32c0ef42b22e5e68dbf390c775ec3c22bb2d501102 android.hardware.neuralnetworks@1.3::IBuffer
+234cc547d63d2f24a447aee0a9a76cab68b31c080adadc5a960598b827a69fa2 android.hardware.neuralnetworks@1.3::IDevice
+058b48f0e2e725bb2b3fa2b7917b0f0a696383d03a4c57afe26f0eadb6a7af28 android.hardware.neuralnetworks@1.3::IPreparedModel
94e803236398bed1febb11cc21051bc42ec003700139b099d6c479e02a7ca3c3 android.hardware.neuralnetworks@1.3::IPreparedModelCallback
-f3c1e7298da628a755b452cd3325e8d0fe867a2debb873069baab6a27434a72d android.hardware.neuralnetworks@1.3::types
+2576ba54711218ce0d7f207baa533fca9af3c630756938ede6e73fe197b7ea38 android.hardware.neuralnetworks@1.3::types
3e01d4446cd69fd1c48f8572efd97487bc179564b32bd795800b97bbe10be37b android.hardware.wifi@1.4::IWifi
c67aaf26a7a40d14ea61e70e20afacbd0bb906df1704d585ac8599fbb69dd44b android.hardware.wifi.hostapd@1.2::IHostapd
11f6448d15336361180391c8ebcdfd2d7cf77b3782d577e594d583aadc9c2877 android.hardware.wifi.hostapd@1.2::types
diff --git a/neuralnetworks/1.3/Android.bp b/neuralnetworks/1.3/Android.bp
index 0b07a58..08e824d 100644
--- a/neuralnetworks/1.3/Android.bp
+++ b/neuralnetworks/1.3/Android.bp
@@ -8,6 +8,7 @@
},
srcs: [
"types.hal",
+ "IBuffer.hal",
"IDevice.hal",
"IPreparedModel.hal",
"IPreparedModelCallback.hal",
diff --git a/neuralnetworks/1.3/IBuffer.hal b/neuralnetworks/1.3/IBuffer.hal
new file mode 100644
index 0000000..84241c5
--- /dev/null
+++ b/neuralnetworks/1.3/IBuffer.hal
@@ -0,0 +1,57 @@
+/*
+ * Copyright (C) 2020 The Android Open Source Project
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+package android.hardware.neuralnetworks@1.3;
+
+import @1.0::ErrorStatus;
+
+/**
+ * This interface represents a device memory buffer.
+ */
+interface IBuffer {
+ /**
+ * Retrieves the content of this buffer to a shared memory region.
+ *
+ * The IBuffer object must have been initialized before the call to IBuffer::copyTo.
+ * For more information on the state of the IBuffer object, refer to IDevice::allocate.
+ *
+ * @param dst The destination shared memory region.
+ * @return status Error status of the call, must be:
+ * - NONE if successful
+ * - DEVICE_UNAVAILABLE if driver is offline or busy
+ * - GENERAL_FAILURE if the IBuffer object is uninitialized, or there is an unspecified
+ * error
+ * - INVALID_ARGUMENT if provided memory is invalid
+ */
+ copyTo(memory dst) generates (ErrorStatus status);
+
+ /**
+ * Sets the content of this buffer from a shared memory region.
+ *
+ * @param src The source shared memory region.
+ * @param dimensions Updated dimensional information. If the dimensions of the IBuffer object
+ * are not fully specified, then the dimensions must be fully specified here. If the
+ * dimensions of the IBuffer object are fully specified, then the dimensions may be empty
+ * here. If dimensions.size() > 0, then all dimensions must be specified here, and any
+ * dimension that was specified in the IBuffer object must have the same value here.
+ * @return status Error status of the call, must be:
+ * - NONE if successful
+ * - DEVICE_UNAVAILABLE if driver is offline or busy
+ * - GENERAL_FAILURE if there is an unspecified error
+ * - INVALID_ARGUMENT if provided memory is invalid, or if the dimensions is invalid
+ */
+ copyFrom(memory src, vec<uint32_t> dimensions) generates (ErrorStatus status);
+};
diff --git a/neuralnetworks/1.3/IDevice.hal b/neuralnetworks/1.3/IDevice.hal
index 1295d6a..9afd778 100644
--- a/neuralnetworks/1.3/IDevice.hal
+++ b/neuralnetworks/1.3/IDevice.hal
@@ -22,6 +22,12 @@
import @1.2::DeviceType;
import @1.2::Extension;
import @1.2::IDevice;
+import BufferDesc;
+import BufferRole;
+import Capabilities;
+import Model;
+import IBuffer;
+import IPreparedModel;
import IPreparedModelCallback;
/**
@@ -247,4 +253,61 @@
uint8_t[Constant:BYTE_SIZE_OF_CACHE_TOKEN] token,
IPreparedModelCallback callback)
generates (ErrorStatus status);
+
+ /**
+ * Allocates a driver-managed buffer with the properties specified by the buffer descriptor
+ * as well as the input and output roles.
+ *
+ * The allocate function must verify its inputs are correct. If there is an error, or if a
+ * certain role or property is not supported by the driver, the allocate
+ * function must return with an appropriate ErrorStatus, a nullptr as the IBuffer, and 0 as the
+ * buffer token. If the allocation is successful, this method must return with ErrorStatus::NONE
+ * and the produced IBuffer with a positive token identifying the allocated buffer. A successful
+ * allocation must accommodate all of the specified roles and buffer properties.
+ *
+ * The buffer is allocated to an uninitialized state. An uninitialized buffer may only be used
+ * in ways that are specified by outputRoles. A buffer is initialized after it is used as an
+ * output in a successful execution, or after a successful invocation of IBuffer::copyFrom on
+ * the buffer. An initialized buffer may be used according to all roles specified in inputRoles
+ * and outputRoles. A buffer will return to the uninitialized state if it is used as an output
+ * in a failed execution, or after a failed invocation of IBuffer::copyFrom on the buffer.
+ *
+ * The dimensions of the buffer can be deduced from the buffer descriptor as well as the
+ * dimensions of the corresponding model operands of the input and output roles. The dimensions
+ * or rank of the buffer may be unknown at this stage. As such, some driver services may only
+ * create a placeholder and defer the actual allocation until execution time. Note that the
+ * same buffer may be used for different shapes of outputs on different executions. When the
+ * buffer is used as an input, the input shape must be the same as the output shape from the
+ * last execution using this buffer as an output.
+ *
+ * The driver must apply proper validatation upon every usage of the buffer, and must fail the
+ * execution immediately if the usage is illegal.
+ *
+ * @param desc A buffer descriptor specifying the properties of the buffer to allocate.
+ * @param preparedModels A vector of IPreparedModel objects. Must only contain IPreparedModel
+ * objects from the same IDevice as this method is being invoked on.
+ * @param inputRoles A vector of roles with each specifying an input to a prepared model.
+ * @param outputRoles A vector of roles with each specifying an output to a prepared model.
+ * Each role specified in inputRoles and outputRoles must be unique. The corresponding
+ * model operands of the roles must have the same OperandType, scale, zero point, and
+ * ExtraParams. The dimensions of the operands and the dimensions specified in the buffer
+ * descriptor must be compatible with each other. Two dimensions are incompatible if there
+ * is at least one axis that is fully specified in both but has different values.
+ * @return status Error status of the buffer allocation. Must be:
+ * - NONE if successful
+ * - DEVICE_UNAVAILABLE if driver is offline or busy
+ * - GENERAL_FAILURE if a certain buffer property or a certain role is not supported,
+ * or if there is an unspecified error
+ * - INVALID_ARGUMENT if one of the input arguments is invalid
+ * @return buffer The allocated IBuffer object. If the buffer was unable to be allocated
+ * due to an error, nullptr must be returned.
+ * @return token A positive token identifying the allocated buffer. The same token will be
+ * provided when referencing the buffer as one of the memory pools in the request of an
+ * execution. The token must not collide with the tokens of other IBuffer objects that are
+ * currently alive in the same driver service. If the buffer was unable to be allocated
+ * due to an error, the token must be 0.
+ */
+ allocate(BufferDesc desc, vec<IPreparedModel> preparedModels, vec<BufferRole> inputRoles,
+ vec<BufferRole> outputRoles)
+ generates (ErrorStatus status, IBuffer buffer, int32_t token);
};
diff --git a/neuralnetworks/1.3/IPreparedModel.hal b/neuralnetworks/1.3/IPreparedModel.hal
index 7aea416..00adc1f 100644
--- a/neuralnetworks/1.3/IPreparedModel.hal
+++ b/neuralnetworks/1.3/IPreparedModel.hal
@@ -17,12 +17,12 @@
package android.hardware.neuralnetworks@1.3;
import @1.0::ErrorStatus;
-import @1.0::Request;
import @1.2::IExecutionCallback;
import @1.2::IPreparedModel;
import @1.2::MeasureTiming;
import @1.2::OutputShape;
import @1.2::Timing;
+import Request;
/**
* IPreparedModel describes a model that has been prepared for execution and
@@ -33,7 +33,8 @@
* Launches an asynchronous execution on a prepared model.
*
* The execution is performed asynchronously with respect to the caller.
- * execute_1_3 must verify the inputs to the function are correct. If there is
+ * execute_1_3 must verify the inputs to the function are correct, and the usages
+ * of memory pools allocated by IDevice::allocate are valid. If there is
* an error, execute_1_3 must immediately invoke the callback with the
* appropriate ErrorStatus value, then return with the same ErrorStatus. If
* the inputs to the function are valid and there is no error, execute_1_3 must
@@ -95,7 +96,8 @@
*
* The execution is performed synchronously with respect to the caller.
* executeSynchronously_1_3 must verify the inputs to the function are
- * correct. If there is an error, executeSynchronously_1_3 must immediately
+ * correct, and the usages of memory pools allocated by IDevice::allocate
+ * are valid. If there is an error, executeSynchronously_1_3 must immediately
* return with the appropriate ErrorStatus value. If the inputs to the
* function are valid and there is no error, executeSynchronously_1_3 must
* perform the execution, and must not return until the execution is
diff --git a/neuralnetworks/1.3/types.hal b/neuralnetworks/1.3/types.hal
index 62c5833..6c8fe43 100644
--- a/neuralnetworks/1.3/types.hal
+++ b/neuralnetworks/1.3/types.hal
@@ -19,6 +19,7 @@
import @1.0::DataLocation;
import @1.0::OperandLifeTime;
import @1.0::PerformanceInfo;
+import @1.0::RequestArgument;
import @1.2::OperandType;
import @1.2::OperationType;
import @1.2::SymmPerChannelQuantParams;
@@ -5205,3 +5206,92 @@
LOW_BITS_TYPE = 16,
};
};
+
+/**
+ * A buffer descriptor. Describes the properties of a buffer.
+ */
+struct BufferDesc {
+ /**
+ * Dimensions of the buffer. May have unknown dimensions or rank. A buffer with some number
+ * of unspecified dimensions is represented by setting each unspecified dimension to 0. A
+ * buffer with unspecified rank is represented by providing an empty dimensions vector.
+ */
+ vec<uint32_t> dimensions;
+};
+
+/**
+ * Describes a role of an input or output to a prepared model.
+ */
+struct BufferRole {
+ /**
+ * The index of the IPreparedModel within the "preparedModel" argument passed in
+ * IDevice::allocate.
+ */
+ uint32_t modelIndex;
+
+ /**
+ * The index of the input or output operand.
+ */
+ uint32_t ioIndex;
+
+ /**
+ * A floating-point value within the range (0.0, 1.0]. Describes how likely the
+ * buffer is to be used in the specified role. This is provided as a hint to
+ * optimize the case when multiple roles prefer different buffer locations or data
+ * layouts.
+ */
+ float frequency;
+};
+
+/**
+ * Inputs to be sent to and outputs to be retrieved from a prepared model.
+ *
+ * A Request serves two primary tasks:
+ * 1) Provides the input and output data to be used when executing the model.
+ * 2) Specifies any updates to the input operand metadata that were left
+ * unspecified at model preparation time.
+ *
+ * An output must not overlap with any other output, with an input, or
+ * with an operand of lifetime CONSTANT_REFERENCE.
+ */
+struct Request {
+ /**
+ * Input data and information to be used in the execution of a prepared
+ * model.
+ *
+ * The index of the input corresponds to the index in Model.inputIndexes.
+ * E.g., input[i] corresponds to Model.inputIndexes[i].
+ */
+ vec<RequestArgument> inputs;
+
+ /**
+ * Output data and information to be used in the execution of a prepared
+ * model.
+ *
+ * The index of the output corresponds to the index in Model.outputIndexes.
+ * E.g., output[i] corresponds to Model.outputIndexes[i].
+ */
+ vec<RequestArgument> outputs;
+
+ /**
+ * A memory pool.
+ */
+ safe_union MemoryPool {
+ /**
+ * Specifies a client-managed shared memory pool.
+ */
+ memory hidlMemory;
+
+ /**
+ * Specifies a driver-managed buffer. It is the token returned from IDevice::allocate,
+ * and is specific to the IDevice object.
+ */
+ int32_t token;
+ };
+
+ /**
+ * A collection of memory pools containing operand data for both the
+ * inputs and the outputs to a model.
+ */
+ vec<MemoryPool> pools;
+};
diff --git a/neuralnetworks/1.3/types.t b/neuralnetworks/1.3/types.t
index 0d20d06..b1c72a9 100644
--- a/neuralnetworks/1.3/types.t
+++ b/neuralnetworks/1.3/types.t
@@ -21,6 +21,7 @@
import @1.0::DataLocation;
import @1.0::OperandLifeTime;
import @1.0::PerformanceInfo;
+import @1.0::RequestArgument;
import @1.2::OperandType;
import @1.2::OperationType;
import @1.2::SymmPerChannelQuantParams;
@@ -389,3 +390,92 @@
LOW_BITS_TYPE = 16,
};
};
+
+/**
+ * A buffer descriptor. Describes the properties of a buffer.
+ */
+struct BufferDesc {
+ /**
+ * Dimensions of the buffer. May have unknown dimensions or rank. A buffer with some number
+ * of unspecified dimensions is represented by setting each unspecified dimension to 0. A
+ * buffer with unspecified rank is represented by providing an empty dimensions vector.
+ */
+ vec<uint32_t> dimensions;
+};
+
+/**
+ * Describes a role of an input or output to a prepared model.
+ */
+struct BufferRole {
+ /**
+ * The index of the IPreparedModel within the "preparedModel" argument passed in
+ * IDevice::allocate.
+ */
+ uint32_t modelIndex;
+
+ /**
+ * The index of the input or output operand.
+ */
+ uint32_t ioIndex;
+
+ /**
+ * A floating-point value within the range (0.0, 1.0]. Describes how likely the
+ * buffer is to be used in the specified role. This is provided as a hint to
+ * optimize the case when multiple roles prefer different buffer locations or data
+ * layouts.
+ */
+ float frequency;
+};
+
+/**
+ * Inputs to be sent to and outputs to be retrieved from a prepared model.
+ *
+ * A Request serves two primary tasks:
+ * 1) Provides the input and output data to be used when executing the model.
+ * 2) Specifies any updates to the input operand metadata that were left
+ * unspecified at model preparation time.
+ *
+ * An output must not overlap with any other output, with an input, or
+ * with an operand of lifetime CONSTANT_REFERENCE.
+ */
+struct Request {
+ /**
+ * Input data and information to be used in the execution of a prepared
+ * model.
+ *
+ * The index of the input corresponds to the index in Model.inputIndexes.
+ * E.g., input[i] corresponds to Model.inputIndexes[i].
+ */
+ vec<RequestArgument> inputs;
+
+ /**
+ * Output data and information to be used in the execution of a prepared
+ * model.
+ *
+ * The index of the output corresponds to the index in Model.outputIndexes.
+ * E.g., output[i] corresponds to Model.outputIndexes[i].
+ */
+ vec<RequestArgument> outputs;
+
+ /**
+ * A memory pool.
+ */
+ safe_union MemoryPool {
+ /**
+ * Specifies a client-managed shared memory pool.
+ */
+ memory hidlMemory;
+
+ /**
+ * Specifies a driver-managed buffer. It is the token returned from IDevice::allocate,
+ * and is specific to the IDevice object.
+ */
+ int32_t token;
+ };
+
+ /**
+ * A collection of memory pools containing operand data for both the
+ * inputs and the outputs to a model.
+ */
+ vec<MemoryPool> pools;
+};
diff --git a/neuralnetworks/1.3/vts/functional/CompilationCachingTests.cpp b/neuralnetworks/1.3/vts/functional/CompilationCachingTests.cpp
index 60992d5..fe8d907 100644
--- a/neuralnetworks/1.3/vts/functional/CompilationCachingTests.cpp
+++ b/neuralnetworks/1.3/vts/functional/CompilationCachingTests.cpp
@@ -456,7 +456,7 @@
}
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
}
TEST_P(CompilationCachingTest, CacheSavingAndRetrievalNonZeroOffset) {
@@ -518,7 +518,7 @@
}
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
}
TEST_P(CompilationCachingTest, SaveToCacheInvalidNumCache) {
@@ -539,7 +539,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -563,7 +563,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -586,7 +586,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -610,7 +610,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -721,7 +721,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -745,7 +745,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -768,7 +768,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -792,7 +792,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -904,7 +904,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -926,7 +926,7 @@
saveModelToCache(model, modelCache, dataCache, &preparedModel);
ASSERT_NE(preparedModel, nullptr);
// Execute and verify results.
- EvaluatePreparedModel(preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModel, /*testKind=*/TestKind::GENERAL);
// Check if prepareModelFromCache fails.
preparedModel = nullptr;
ErrorStatus status;
@@ -1070,7 +1070,8 @@
ASSERT_EQ(preparedModel, nullptr);
} else {
ASSERT_NE(preparedModel, nullptr);
- EvaluatePreparedModel(preparedModel, testModelAdd, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModelAdd,
+ /*testKind=*/TestKind::GENERAL);
}
}
}
@@ -1131,7 +1132,8 @@
ASSERT_EQ(preparedModel, nullptr);
} else {
ASSERT_NE(preparedModel, nullptr);
- EvaluatePreparedModel(preparedModel, testModelAdd, /*testKind=*/TestKind::GENERAL);
+ EvaluatePreparedModel(kDevice, preparedModel, testModelAdd,
+ /*testKind=*/TestKind::GENERAL);
}
}
}
diff --git a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
index eced063..4f747f4 100644
--- a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
+++ b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.cpp
@@ -60,7 +60,7 @@
using V1_0::DataLocation;
using V1_0::ErrorStatus;
using V1_0::OperandLifeTime;
-using V1_0::Request;
+using V1_0::RequestArgument;
using V1_1::ExecutionPreference;
using V1_2::Constant;
using V1_2::MeasureTiming;
@@ -76,27 +76,118 @@
enum class OutputType { FULLY_SPECIFIED, UNSPECIFIED, INSUFFICIENT };
+enum class MemoryType { SHARED, DEVICE };
+
+enum class IOType { INPUT, OUTPUT };
+
struct TestConfig {
Executor executor;
MeasureTiming measureTiming;
OutputType outputType;
+ MemoryType memoryType;
// `reportSkipping` indicates if a test should print an info message in case
// it is skipped. The field is set to true by default and is set to false in
// quantization coupling tests to suppress skipping a test
bool reportSkipping;
- TestConfig(Executor executor, MeasureTiming measureTiming, OutputType outputType)
+ TestConfig(Executor executor, MeasureTiming measureTiming, OutputType outputType,
+ MemoryType memoryType)
: executor(executor),
measureTiming(measureTiming),
outputType(outputType),
+ memoryType(memoryType),
reportSkipping(true) {}
TestConfig(Executor executor, MeasureTiming measureTiming, OutputType outputType,
- bool reportSkipping)
+ MemoryType memoryType, bool reportSkipping)
: executor(executor),
measureTiming(measureTiming),
outputType(outputType),
+ memoryType(memoryType),
reportSkipping(reportSkipping) {}
};
+class DeviceMemoryAllocator {
+ public:
+ DeviceMemoryAllocator(const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
+ const TestModel& testModel)
+ : kDevice(device), kPreparedModel(preparedModel), kTestModel(testModel) {}
+
+ // Allocate device memory for a target input/output operand.
+ // Return {IBuffer object, token} if successful.
+ // Return {nullptr, 0} if device memory is not supported.
+ template <IOType ioType>
+ std::pair<sp<IBuffer>, int32_t> allocate(uint32_t index) {
+ std::pair<sp<IBuffer>, int32_t> buffer;
+ allocateInternal<ioType>(index, &buffer);
+ return buffer;
+ }
+
+ private:
+ template <IOType ioType>
+ void allocateInternal(uint32_t index, std::pair<sp<IBuffer>, int32_t>* result) {
+ ASSERT_NE(result, nullptr);
+
+ // Prepare arguments.
+ BufferRole role = {.modelIndex = 0, .ioIndex = index, .frequency = 1.0f};
+ hidl_vec<BufferRole> inputRoles, outputRoles;
+ if constexpr (ioType == IOType::INPUT) {
+ inputRoles = {role};
+ } else {
+ outputRoles = {role};
+ }
+
+ // Allocate device memory.
+ ErrorStatus status;
+ sp<IBuffer> buffer;
+ int32_t token;
+ const auto ret = kDevice->allocate(
+ {}, {kPreparedModel}, inputRoles, outputRoles,
+ [&status, &buffer, &token](ErrorStatus error, const sp<IBuffer>& buf, int32_t tok) {
+ status = error;
+ buffer = buf;
+ token = tok;
+ });
+
+ // Check allocation results.
+ ASSERT_TRUE(ret.isOk());
+ if (status == ErrorStatus::NONE) {
+ ASSERT_NE(buffer, nullptr);
+ ASSERT_GT(token, 0);
+ } else {
+ ASSERT_EQ(status, ErrorStatus::GENERAL_FAILURE);
+ ASSERT_EQ(buffer, nullptr);
+ ASSERT_EQ(token, 0);
+ }
+
+ // Initialize input data from TestBuffer.
+ if constexpr (ioType == IOType::INPUT) {
+ if (buffer != nullptr) {
+ // TestBuffer -> Shared memory.
+ const auto& testBuffer = kTestModel.operands[kTestModel.inputIndexes[index]].data;
+ ASSERT_GT(testBuffer.size(), 0);
+ hidl_memory tmp = nn::allocateSharedMemory(testBuffer.size());
+ sp<IMemory> inputMemory = mapMemory(tmp);
+ ASSERT_NE(inputMemory.get(), nullptr);
+ uint8_t* inputPtr =
+ static_cast<uint8_t*>(static_cast<void*>(inputMemory->getPointer()));
+ ASSERT_NE(inputPtr, nullptr);
+ const uint8_t* begin = testBuffer.get<uint8_t>();
+ const uint8_t* end = begin + testBuffer.size();
+ std::copy(begin, end, inputPtr);
+
+ // Shared memory -> IBuffer.
+ auto ret = buffer->copyFrom(tmp, {});
+ ASSERT_TRUE(ret.isOk());
+ ASSERT_EQ(static_cast<ErrorStatus>(ret), ErrorStatus::NONE);
+ }
+ }
+ *result = {std::move(buffer), token};
+ }
+
+ const sp<IDevice> kDevice;
+ const sp<IPreparedModel> kPreparedModel;
+ const TestModel& kTestModel;
+};
+
} // namespace
Model createModel(const TestModel& testModel) {
@@ -205,6 +296,161 @@
}
}
+constexpr uint32_t kInputPoolIndex = 0;
+constexpr uint32_t kOutputPoolIndex = 1;
+constexpr uint32_t kDeviceMemoryBeginIndex = 2;
+
+static std::pair<Request, std::vector<sp<IBuffer>>> createRequest(
+ const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
+ const TestModel& testModel, bool preferDeviceMemory) {
+ // Memory pools are organized as:
+ // - 0: Input shared memory pool
+ // - 1: Output shared memory pool
+ // - [2, 2+i): Input device memories
+ // - [2+i, 2+i+o): Output device memories
+ DeviceMemoryAllocator allocator(device, preparedModel, testModel);
+ std::vector<sp<IBuffer>> buffers;
+ std::vector<int32_t> tokens;
+
+ // Model inputs.
+ hidl_vec<RequestArgument> inputs(testModel.inputIndexes.size());
+ size_t inputSize = 0;
+ for (uint32_t i = 0; i < testModel.inputIndexes.size(); i++) {
+ const auto& op = testModel.operands[testModel.inputIndexes[i]];
+ if (op.data.size() == 0) {
+ // Omitted input.
+ inputs[i] = {.hasNoValue = true};
+ continue;
+ } else if (preferDeviceMemory) {
+ SCOPED_TRACE("Input index = " + std::to_string(i));
+ auto [buffer, token] = allocator.allocate<IOType::INPUT>(i);
+ if (buffer != nullptr) {
+ DataLocation loc = {.poolIndex = static_cast<uint32_t>(buffers.size() +
+ kDeviceMemoryBeginIndex)};
+ buffers.push_back(std::move(buffer));
+ tokens.push_back(token);
+ inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+ continue;
+ }
+ }
+
+ // Reserve shared memory for input.
+ DataLocation loc = {.poolIndex = kInputPoolIndex,
+ .offset = static_cast<uint32_t>(inputSize),
+ .length = static_cast<uint32_t>(op.data.size())};
+ inputSize += op.data.alignedSize();
+ inputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+ }
+
+ // Model outputs.
+ hidl_vec<RequestArgument> outputs(testModel.outputIndexes.size());
+ size_t outputSize = 0;
+ for (uint32_t i = 0; i < testModel.outputIndexes.size(); i++) {
+ const auto& op = testModel.operands[testModel.outputIndexes[i]];
+ if (preferDeviceMemory) {
+ SCOPED_TRACE("Output index = " + std::to_string(i));
+ auto [buffer, token] = allocator.allocate<IOType::OUTPUT>(i);
+ if (buffer != nullptr) {
+ DataLocation loc = {.poolIndex = static_cast<uint32_t>(buffers.size() +
+ kDeviceMemoryBeginIndex)};
+ buffers.push_back(std::move(buffer));
+ tokens.push_back(token);
+ outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+ continue;
+ }
+ }
+
+ // In the case of zero-sized output, we should at least provide a one-byte buffer.
+ // This is because zero-sized tensors are only supported internally to the driver, or
+ // reported in output shapes. It is illegal for the client to pre-specify a zero-sized
+ // tensor as model output. Otherwise, we will have two semantic conflicts:
+ // - "Zero dimension" conflicts with "unspecified dimension".
+ // - "Omitted operand buffer" conflicts with "zero-sized operand buffer".
+ size_t bufferSize = std::max<size_t>(op.data.size(), 1);
+
+ // Reserve shared memory for output.
+ DataLocation loc = {.poolIndex = kOutputPoolIndex,
+ .offset = static_cast<uint32_t>(outputSize),
+ .length = static_cast<uint32_t>(bufferSize)};
+ outputSize += op.data.size() == 0 ? TestBuffer::kAlignment : op.data.alignedSize();
+ outputs[i] = {.hasNoValue = false, .location = loc, .dimensions = {}};
+ }
+
+ // Memory pools.
+ hidl_vec<Request::MemoryPool> pools(kDeviceMemoryBeginIndex + buffers.size());
+ pools[kInputPoolIndex].hidlMemory(nn::allocateSharedMemory(std::max<size_t>(inputSize, 1)));
+ pools[kOutputPoolIndex].hidlMemory(nn::allocateSharedMemory(std::max<size_t>(outputSize, 1)));
+ CHECK_NE(pools[kInputPoolIndex].hidlMemory().size(), 0u);
+ CHECK_NE(pools[kOutputPoolIndex].hidlMemory().size(), 0u);
+ for (uint32_t i = 0; i < buffers.size(); i++) {
+ pools[kDeviceMemoryBeginIndex + i].token(tokens[i]);
+ }
+
+ // Copy input data to the input shared memory pool.
+ sp<IMemory> inputMemory = mapMemory(pools[kInputPoolIndex].hidlMemory());
+ CHECK(inputMemory.get() != nullptr);
+ uint8_t* inputPtr = static_cast<uint8_t*>(static_cast<void*>(inputMemory->getPointer()));
+ CHECK(inputPtr != nullptr);
+ for (uint32_t i = 0; i < testModel.inputIndexes.size(); i++) {
+ if (!inputs[i].hasNoValue && inputs[i].location.poolIndex == kInputPoolIndex) {
+ const auto& op = testModel.operands[testModel.inputIndexes[i]];
+ const uint8_t* begin = op.data.get<uint8_t>();
+ const uint8_t* end = begin + op.data.size();
+ std::copy(begin, end, inputPtr + inputs[i].location.offset);
+ }
+ }
+
+ Request request = {
+ .inputs = std::move(inputs), .outputs = std::move(outputs), .pools = std::move(pools)};
+ return {std::move(request), std::move(buffers)};
+}
+
+// Get a TestBuffer with data copied from an IBuffer object.
+static void getBuffer(const sp<IBuffer>& buffer, size_t size, TestBuffer* testBuffer) {
+ // IBuffer -> Shared memory.
+ hidl_memory tmp = nn::allocateSharedMemory(size);
+ const auto ret = buffer->copyTo(tmp);
+ ASSERT_TRUE(ret.isOk());
+ ASSERT_EQ(static_cast<ErrorStatus>(ret), ErrorStatus::NONE);
+
+ // Shared memory -> TestBuffer.
+ sp<IMemory> outputMemory = mapMemory(tmp);
+ ASSERT_NE(outputMemory.get(), nullptr);
+ uint8_t* outputPtr = static_cast<uint8_t*>(static_cast<void*>(outputMemory->getPointer()));
+ ASSERT_NE(outputPtr, nullptr);
+ ASSERT_NE(testBuffer, nullptr);
+ *testBuffer = TestBuffer(size, outputPtr);
+}
+
+static std::vector<TestBuffer> getOutputBuffers(const TestModel& testModel, const Request& request,
+ const std::vector<sp<IBuffer>>& buffers) {
+ sp<IMemory> outputMemory = mapMemory(request.pools[kOutputPoolIndex].hidlMemory());
+ CHECK(outputMemory.get() != nullptr);
+ uint8_t* outputPtr = static_cast<uint8_t*>(static_cast<void*>(outputMemory->getPointer()));
+ CHECK(outputPtr != nullptr);
+
+ // Copy out output results.
+ std::vector<TestBuffer> outputBuffers;
+ for (uint32_t i = 0; i < request.outputs.size(); i++) {
+ const auto& outputLoc = request.outputs[i].location;
+ if (outputLoc.poolIndex == kOutputPoolIndex) {
+ outputBuffers.emplace_back(outputLoc.length, outputPtr + outputLoc.offset);
+ } else {
+ const auto& op = testModel.operands[testModel.outputIndexes[i]];
+ if (op.data.size() == 0) {
+ outputBuffers.emplace_back();
+ } else {
+ SCOPED_TRACE("Output index = " + std::to_string(i));
+ const uint32_t bufferIndex = outputLoc.poolIndex - kDeviceMemoryBeginIndex;
+ TestBuffer buffer;
+ getBuffer(buffers[bufferIndex], op.data.size(), &buffer);
+ outputBuffers.push_back(std::move(buffer));
+ }
+ }
+ }
+ return outputBuffers;
+}
+
static Return<ErrorStatus> ExecutePreparedModel(const sp<IPreparedModel>& preparedModel,
const Request& request, MeasureTiming measure,
sp<ExecutionCallback>& callback) {
@@ -234,8 +480,9 @@
std::chrono::microseconds{0});
}
-void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,
- const TestConfig& testConfig, bool* skipped = nullptr) {
+void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
+ const TestModel& testModel, const TestConfig& testConfig,
+ bool* skipped = nullptr) {
if (skipped != nullptr) {
*skipped = false;
}
@@ -245,7 +492,13 @@
return;
}
- Request request = createRequest(testModel);
+ auto [request, buffers] =
+ createRequest(device, preparedModel, testModel,
+ /*preferDeviceMemory=*/testConfig.memoryType == MemoryType::DEVICE);
+ // Skip if testing memory domain but no device memory has been allocated.
+ if (testConfig.memoryType == MemoryType::DEVICE && buffers.empty()) {
+ return;
+ }
if (testConfig.outputType == OutputType::INSUFFICIENT) {
makeOutputInsufficientSize(/*outputIndex=*/0, &request);
}
@@ -284,23 +537,29 @@
break;
}
case Executor::BURST: {
+ // TODO(butlermichael): Check if we need to test burst in V1_3 if the interface remains
+ // V1_2.
SCOPED_TRACE("burst");
+ // check compliance
+ ASSERT_TRUE(nn::compliantWithV1_0(request));
+ V1_0::Request request10 = nn::convertToV1_0(request);
+
// create burst
const std::shared_ptr<::android::nn::ExecutionBurstController> controller =
CreateBurst(preparedModel);
ASSERT_NE(nullptr, controller.get());
// create memory keys
- std::vector<intptr_t> keys(request.pools.size());
+ std::vector<intptr_t> keys(request10.pools.size());
for (size_t i = 0; i < keys.size(); ++i) {
- keys[i] = reinterpret_cast<intptr_t>(&request.pools[i]);
+ keys[i] = reinterpret_cast<intptr_t>(&request10.pools[i]);
}
// execute burst
int n;
std::tie(n, outputShapes, timing, std::ignore) =
- controller->compute(request, testConfig.measureTiming, keys);
+ controller->compute(request10, testConfig.measureTiming, keys);
executionStatus = nn::convertResultCodeToErrorStatus(n);
break;
@@ -361,17 +620,18 @@
}
// Retrieve execution results.
- const std::vector<TestBuffer> outputs = getOutputBuffers(request);
+ const std::vector<TestBuffer> outputs = getOutputBuffers(testModel, request, buffers);
// We want "close-enough" results.
checkResults(testModel, outputs);
}
-void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel, const TestModel& testModel,
- TestKind testKind) {
+void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
+ const TestModel& testModel, TestKind testKind) {
std::vector<OutputType> outputTypesList;
std::vector<MeasureTiming> measureTimingList;
std::vector<Executor> executorList;
+ MemoryType memoryType = MemoryType::SHARED;
switch (testKind) {
case TestKind::GENERAL: {
@@ -384,6 +644,12 @@
measureTimingList = {MeasureTiming::NO, MeasureTiming::YES};
executorList = {Executor::ASYNC, Executor::SYNC, Executor::BURST};
} break;
+ case TestKind::MEMORY_DOMAIN: {
+ outputTypesList = {OutputType::FULLY_SPECIFIED};
+ measureTimingList = {MeasureTiming::NO};
+ executorList = {Executor::ASYNC, Executor::SYNC};
+ memoryType = MemoryType::DEVICE;
+ } break;
case TestKind::QUANTIZATION_COUPLING: {
LOG(FATAL) << "Wrong TestKind for EvaluatePreparedModel";
return;
@@ -393,14 +659,15 @@
for (const OutputType outputType : outputTypesList) {
for (const MeasureTiming measureTiming : measureTimingList) {
for (const Executor executor : executorList) {
- const TestConfig testConfig(executor, measureTiming, outputType);
- EvaluatePreparedModel(preparedModel, testModel, testConfig);
+ const TestConfig testConfig(executor, measureTiming, outputType, memoryType);
+ EvaluatePreparedModel(device, preparedModel, testModel, testConfig);
}
}
}
}
-void EvaluatePreparedCoupledModels(const sp<IPreparedModel>& preparedModel,
+void EvaluatePreparedCoupledModels(const sp<IDevice>& device,
+ const sp<IPreparedModel>& preparedModel,
const TestModel& testModel,
const sp<IPreparedModel>& preparedCoupledModel,
const TestModel& coupledModel) {
@@ -411,12 +678,12 @@
for (const OutputType outputType : outputTypesList) {
for (const MeasureTiming measureTiming : measureTimingList) {
for (const Executor executor : executorList) {
- const TestConfig testConfig(executor, measureTiming, outputType,
+ const TestConfig testConfig(executor, measureTiming, outputType, MemoryType::SHARED,
/*reportSkipping=*/false);
bool baseSkipped = false;
- EvaluatePreparedModel(preparedModel, testModel, testConfig, &baseSkipped);
+ EvaluatePreparedModel(device, preparedModel, testModel, testConfig, &baseSkipped);
bool coupledSkipped = false;
- EvaluatePreparedModel(preparedCoupledModel, coupledModel, testConfig,
+ EvaluatePreparedModel(device, preparedCoupledModel, coupledModel, testConfig,
&coupledSkipped);
ASSERT_EQ(baseSkipped, coupledSkipped);
if (baseSkipped) {
@@ -441,15 +708,12 @@
sp<IPreparedModel> preparedModel;
switch (testKind) {
- case TestKind::GENERAL: {
+ case TestKind::GENERAL:
+ case TestKind::DYNAMIC_SHAPE:
+ case TestKind::MEMORY_DOMAIN: {
createPreparedModel(device, model, &preparedModel);
if (preparedModel == nullptr) return;
- EvaluatePreparedModel(preparedModel, testModel, TestKind::GENERAL);
- } break;
- case TestKind::DYNAMIC_SHAPE: {
- createPreparedModel(device, model, &preparedModel);
- if (preparedModel == nullptr) return;
- EvaluatePreparedModel(preparedModel, testModel, TestKind::DYNAMIC_SHAPE);
+ EvaluatePreparedModel(device, preparedModel, testModel, testKind);
} break;
case TestKind::QUANTIZATION_COUPLING: {
ASSERT_TRUE(testModel.hasQuant8CoupledOperands());
@@ -473,7 +737,7 @@
GTEST_SKIP();
}
ASSERT_NE(preparedCoupledModel, nullptr);
- EvaluatePreparedCoupledModels(preparedModel, testModel, preparedCoupledModel,
+ EvaluatePreparedCoupledModels(device, preparedModel, testModel, preparedCoupledModel,
signedQuantizedModel);
} break;
}
@@ -499,6 +763,9 @@
// Tag for the dynamic output shape tests
class DynamicOutputShapeTest : public GeneratedTest {};
+// Tag for the memory domain tests
+class MemoryDomainTest : public GeneratedTest {};
+
// Tag for the dynamic output shape tests
class QuantizationCouplingTest : public GeneratedTest {};
@@ -510,6 +777,10 @@
Execute(kDevice, kTestModel, /*testKind=*/TestKind::DYNAMIC_SHAPE);
}
+TEST_P(MemoryDomainTest, Test) {
+ Execute(kDevice, kTestModel, /*testKind=*/TestKind::MEMORY_DOMAIN);
+}
+
TEST_P(QuantizationCouplingTest, Test) {
Execute(kDevice, kTestModel, /*testKind=*/TestKind::QUANTIZATION_COUPLING);
}
@@ -520,6 +791,9 @@
INSTANTIATE_GENERATED_TEST(DynamicOutputShapeTest,
[](const TestModel& testModel) { return !testModel.expectFailure; });
+INSTANTIATE_GENERATED_TEST(MemoryDomainTest,
+ [](const TestModel& testModel) { return !testModel.expectFailure; });
+
INSTANTIATE_GENERATED_TEST(QuantizationCouplingTest, [](const TestModel& testModel) {
return testModel.hasQuant8CoupledOperands() && testModel.operations.size() == 1;
});
diff --git a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h
index ad6323f..2273e3b 100644
--- a/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h
+++ b/neuralnetworks/1.3/vts/functional/GeneratedTestHarness.h
@@ -62,13 +62,15 @@
GENERAL,
// Same as GENERAL but sets dimensions for the output tensors to zeros
DYNAMIC_SHAPE,
+ // Same as GENERAL but use device memories for inputs and outputs
+ MEMORY_DOMAIN,
// Tests if quantized model with TENSOR_QUANT8_ASYMM produces the same result
// (OK/SKIPPED/FAILED) as the model with all such tensors converted to
// TENSOR_QUANT8_ASYMM_SIGNED.
QUANTIZATION_COUPLING
};
-void EvaluatePreparedModel(const sp<IPreparedModel>& preparedModel,
+void EvaluatePreparedModel(const sp<IDevice>& device, const sp<IPreparedModel>& preparedModel,
const test_helper::TestModel& testModel, TestKind testKind);
} // namespace android::hardware::neuralnetworks::V1_3::vts::functional
diff --git a/neuralnetworks/1.3/vts/functional/ValidateRequest.cpp b/neuralnetworks/1.3/vts/functional/ValidateRequest.cpp
index 8092d04..96dc589 100644
--- a/neuralnetworks/1.3/vts/functional/ValidateRequest.cpp
+++ b/neuralnetworks/1.3/vts/functional/ValidateRequest.cpp
@@ -28,7 +28,6 @@
namespace android::hardware::neuralnetworks::V1_3::vts::functional {
using V1_0::ErrorStatus;
-using V1_0::Request;
using V1_2::MeasureTiming;
using V1_2::OutputShape;
using V1_2::Timing;
@@ -93,9 +92,13 @@
}
// burst
+ // TODO(butlermichael): Check if we need to test burst in V1_3 if the interface remains V1_2.
{
SCOPED_TRACE(message + " [burst]");
+ ASSERT_TRUE(nn::compliantWithV1_0(request));
+ V1_0::Request request10 = nn::convertToV1_0(request);
+
// create burst
std::shared_ptr<::android::nn::ExecutionBurstController> burst =
android::nn::ExecutionBurstController::create(preparedModel,
@@ -103,13 +106,13 @@
ASSERT_NE(nullptr, burst.get());
// create memory keys
- std::vector<intptr_t> keys(request.pools.size());
+ std::vector<intptr_t> keys(request10.pools.size());
for (size_t i = 0; i < keys.size(); ++i) {
- keys[i] = reinterpret_cast<intptr_t>(&request.pools[i]);
+ keys[i] = reinterpret_cast<intptr_t>(&request10.pools[i]);
}
// execute and verify
- const auto [n, outputShapes, timing, fallback] = burst->compute(request, measure, keys);
+ const auto [n, outputShapes, timing, fallback] = burst->compute(request10, measure, keys);
const ErrorStatus status = nn::convertResultCodeToErrorStatus(n);
EXPECT_EQ(ErrorStatus::INVALID_ARGUMENT, status);
EXPECT_EQ(outputShapes.size(), 0);
@@ -117,7 +120,7 @@
EXPECT_FALSE(fallback);
// additional burst testing
- if (request.pools.size() > 0) {
+ if (request10.pools.size() > 0) {
// valid free
burst->freeMemory(keys.front());
diff --git a/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp b/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp
index 92d8fa7..1140b68 100644
--- a/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp
+++ b/neuralnetworks/1.3/vts/functional/VtsHalNeuralnetworks.cpp
@@ -25,6 +25,7 @@
#include "1.3/Callbacks.h"
#include "GeneratedTestHarness.h"
#include "TestHarness.h"
+#include "Utils.h"
namespace android::hardware::neuralnetworks::V1_3::vts::functional {
@@ -32,7 +33,6 @@
hidl_array<uint8_t, static_cast<uint32_t>(V1_2::Constant::BYTE_SIZE_OF_CACHE_TOKEN)>;
using implementation::PreparedModelCallback;
using V1_0::ErrorStatus;
-using V1_0::Request;
using V1_1::ExecutionPreference;
// internal helper function
@@ -124,9 +124,9 @@
// Forward declaration from ValidateModel.cpp
void validateModel(const sp<IDevice>& device, const Model& model);
// Forward declaration from ValidateRequest.cpp
-void validateRequest(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
+void validateRequest(const sp<IPreparedModel>& preparedModel, const Request& request);
// Forward declaration from ValidateRequest.cpp
-void validateRequestFailure(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
+void validateRequestFailure(const sp<IPreparedModel>& preparedModel, const Request& request);
// Forward declaration from ValidateBurst.cpp
void validateBurst(const sp<IPreparedModel>& preparedModel, const V1_0::Request& request);
@@ -139,7 +139,11 @@
if (preparedModel == nullptr) return;
validateRequest(preparedModel, request);
- validateBurst(preparedModel, request);
+
+ // TODO(butlermichael): Check if we need to test burst in V1_3 if the interface remains V1_2.
+ ASSERT_TRUE(nn::compliantWithV1_0(request));
+ V1_0::Request request10 = nn::convertToV1_0(request);
+ validateBurst(preparedModel, request10);
}
void validateFailure(const sp<IDevice>& device, const Model& model, const Request& request) {
@@ -157,7 +161,7 @@
TEST_P(ValidationTest, Test) {
const Model model = createModel(kTestModel);
- const Request request = createRequest(kTestModel);
+ const Request request = nn::convertToV1_3(createRequest(kTestModel));
if (kTestModel.expectFailure) {
validateFailure(kDevice, model, request);
} else {