From 5b8093c17044e8eaaaa42d96ba4902dee5791be4 Mon Sep 17 00:00:00 2001 From: Cathal Corbett Date: Fri, 22 Oct 2021 11:12:07 +0100 Subject: IVGCVSW-6420: Constant flag in tensor info is not set correctly !android-nn-driver:6532 !armnn-internal-tests:372451 * Made fix to 2 out of 3 ConstTensor() constructors in Tensor.hpp to throw InvalidArgumentException when TensorInfo isConstant parameter is false. * Added new ConstTensor() constructor in Tensor.cpp to accept vector<>.data() using template. * Fixed runtime->GetOutputTensorInfo()/GetInputTensorInfo() methods and called submethods to return TensorInfo& rather than TensorInfo. * Fixed all failing unit tests for CpuRef/CpuAcc/GpuAcc to ensure any ConstTensor created has it's TensorInfo isConstant set to true. * Added unit tests in TensorTest.cpp to ensure ConstTensor constructors throw InvalidArgumentException when TensorInfo isConstat parameter is false. * Added unit test to ensure an empty ConstTensor constructor will set TensorInfo isConatant to true. * Indentation fixes. * Fix to arm_tensor.i to add isConstant parameter to TensorInfo constructor. Added methods IsConstant() and SetConstant(). * Fix to const_tensor.py to throw ValueError when TensorInfo isConstant is set to false when constructing a ConstTensor. * Fixed PyArmnn unit tests to set TensorInfo isConstant to True when ConstTensor is used. * Added unit tests in test_const_tensor.py to ensure ConstTensor constructors throw ValueError when TensorInfo isConstat parameter is false. Signed-off-by: Cathal Corbett Change-Id: I44e440dd0422c366d31bbdbc77ad2b4db0bde148 --- python/pyarmnn/src/pyarmnn/_tensor/const_tensor.py | 19 +++++--- .../src/pyarmnn/_tensor/workload_tensors.py | 1 + .../src/pyarmnn/swig/modules/armnn_tensor.i | 24 +++++++++- python/pyarmnn/test/test_const_tensor.py | 54 ++++++++++++++++------ python/pyarmnn/test/test_runtime.py | 1 + python/pyarmnn/test/test_tensor_info.py | 4 +- 6 files changed, 79 insertions(+), 24 deletions(-) (limited to 'python') diff --git a/python/pyarmnn/src/pyarmnn/_tensor/const_tensor.py b/python/pyarmnn/src/pyarmnn/_tensor/const_tensor.py index 94995bdd8c..ab4305c18e 100644 --- a/python/pyarmnn/src/pyarmnn/_tensor/const_tensor.py +++ b/python/pyarmnn/src/pyarmnn/_tensor/const_tensor.py @@ -59,24 +59,31 @@ class ConstTensor(AnnConstTensor): Raises: TypeError: Unsupported input data type. - ValueError: Unsupported tensor data type and incorrect input data size. + ValueError: Unsupported tensor data type, incorrect input data size and creation of ConstTensor from non-constant TensorInfo. """ self.__memory_area = None # TensorInfo as first argument and numpy array as second if len(args) > 1 and isinstance(args[0], TensorInfo): - if isinstance(args[1], np.ndarray): + if not isinstance(args[1], np.ndarray): + raise TypeError('Data must be provided as a numpy array.') + # if TensorInfo IsConstant is false + elif not args[0].IsConstant(): + raise ValueError('TensorInfo when initializing ConstTensor must be set to constant.') + else: self.__create_memory_area(args[0].GetDataType(), args[0].GetNumBytes(), args[0].GetNumElements(), args[1]) super().__init__(args[0], self.__memory_area.data) - else: - raise TypeError('Data must be provided as a numpy array.') # copy constructor - reference to memory area is passed from copied const # tensor and armnn's copy constructor is called elif len(args) > 0 and isinstance(args[0], (ConstTensor, Tensor)): - self.__memory_area = args[0].get_memory_area() - super().__init__(args[0]) + # if TensorInfo IsConstant is false + if not args[0].GetInfo().IsConstant(): + raise ValueError('TensorInfo of Tensor when initializing ConstTensor must be set to constant.') + else: + self.__memory_area = args[0].get_memory_area() + super().__init__(args[0]) # empty tensor elif len(args) == 0: diff --git a/python/pyarmnn/src/pyarmnn/_tensor/workload_tensors.py b/python/pyarmnn/src/pyarmnn/_tensor/workload_tensors.py index 22b876896d..532db56cc3 100644 --- a/python/pyarmnn/src/pyarmnn/_tensor/workload_tensors.py +++ b/python/pyarmnn/src/pyarmnn/_tensor/workload_tensors.py @@ -54,6 +54,7 @@ def make_input_tensors(inputs_binding_info: List[Tuple], for in_bind_info, in_data in zip(inputs_binding_info, input_data): in_tensor_id = in_bind_info[0] in_tensor_info = in_bind_info[1] + in_tensor_info.SetConstant() input_tensors.append((in_tensor_id, ConstTensor(in_tensor_info, in_data))) return input_tensors diff --git a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i index 0edf67d618..d8ef37d762 100644 --- a/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i +++ b/python/pyarmnn/src/pyarmnn/swig/modules/armnn_tensor.i @@ -111,7 +111,8 @@ public: TensorInfo(const TensorInfo& other); TensorInfo(const TensorShape& shape, DataType dataType, - float quantizationScale = 0.0f, int32_t quantizationOffset = 0); + float quantizationScale = 0.0f, int32_t quantizationOffset = 0, + bool isConstant = False); %feature("docstring", " @@ -223,6 +224,26 @@ public: ") IsQuantized; bool IsQuantized() const; + %feature("docstring", + " + Returns true if the tensor info is constant. + + Returns: + bool: True if the tensor info is constant. + + ") IsConstant; + bool IsConstant() const; + + %feature("docstring", + " + Sets the tensor info to be constant. + + Args: + IsConstant (bool): Sets tensor info to constant. + + ") SetConstant; + void SetConstant(const bool IsConstant = True); + %feature("docstring", @@ -254,6 +275,7 @@ public: + ", IsQuantized: " + std::to_string($self->IsQuantized()) + ", QuantizationScale: " + std::to_string( $self->GetQuantizationScale()) + ", QuantizationOffset: " + std::to_string($self->GetQuantizationOffset()) + + ", IsConstant: " + std::to_string($self->IsConstant()) + ", NumDimensions: " + std::to_string($self->GetNumDimensions()) + ", NumElements: " + std::to_string($self->GetNumElements()) + "}"; return tmp; diff --git a/python/pyarmnn/test/test_const_tensor.py b/python/pyarmnn/test/test_const_tensor.py index fa6327f19c..2358d65918 100644 --- a/python/pyarmnn/test/test_const_tensor.py +++ b/python/pyarmnn/test/test_const_tensor.py @@ -6,8 +6,8 @@ import numpy as np import pyarmnn as ann -def _get_tensor_info(dt): - tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), dt) +def _get_const_tensor_info(dt): + tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), dt, 0.0, 0, True) return tensor_info @@ -23,7 +23,7 @@ def _get_tensor_info(dt): (ann.DataType_QSymmS16, np.random.randint(1, size=(2, 4)).astype(np.int16)) ], ids=['float32', 'float16', 'unsigned int8', 'signed int8', 'signed int8', 'int32', 'int16']) def test_const_tensor_too_many_elements(dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) num_bytes = tensor_info.GetNumBytes() with pytest.raises(ValueError) as err: @@ -43,7 +43,7 @@ def test_const_tensor_too_many_elements(dt, data): (ann.DataType_QSymmS16, np.random.randint(1, size=(2, 2)).astype(np.int16)) ], ids=['float32', 'float16', 'unsigned int8', 'signed int8', 'signed int8', 'int32', 'int16']) def test_const_tensor_too_little_elements(dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) num_bytes = tensor_info.GetNumBytes() with pytest.raises(ValueError) as err: @@ -63,7 +63,7 @@ def test_const_tensor_too_little_elements(dt, data): (ann.DataType_QSymmS16, np.random.randint(1, size=(2, 2, 3, 3)).astype(np.int16)) ], ids=['float32', 'float16', 'unsigned int8', 'signed int8', 'signed int8', 'int32', 'int16']) def test_const_tensor_multi_dimensional_input(dt, data): - tensor = ann.ConstTensor(ann.TensorInfo(ann.TensorShape((2, 2, 3, 3)), dt), data) + tensor = ann.ConstTensor(ann.TensorInfo(ann.TensorShape((2, 2, 3, 3)), dt, 0.0, 0, True), data) assert data.size == tensor.GetNumElements() assert data.nbytes == tensor.GetNumBytes() @@ -72,7 +72,7 @@ def test_const_tensor_multi_dimensional_input(dt, data): def test_create_const_tensor_from_tensor(): - tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), ann.DataType_Float32) + tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), ann.DataType_Float32, 0.0, 0, True) tensor = ann.Tensor(tensor_info) copied_tensor = ann.ConstTensor(tensor) @@ -85,7 +85,7 @@ def test_create_const_tensor_from_tensor(): def test_const_tensor_from_tensor_has_memory_area_access_after_deletion_of_original_tensor(): - tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), ann.DataType_Float32) + tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), ann.DataType_Float32, 0.0, 0, True) tensor = ann.Tensor(tensor_info) tensor.get_memory_area()[0] = 100 @@ -125,7 +125,7 @@ def test_create_const_tensor_incorrect_args(): (-1, np.random.randint(1, size=(2, 3)).astype(np.float32)), ], ids=['unknown']) def test_const_tensor_unsupported_datatype(dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) with pytest.raises(ValueError) as err: ann.ConstTensor(tensor_info, data) @@ -142,7 +142,7 @@ def test_const_tensor_unsupported_datatype(dt, data): (ann.DataType_QSymmS8, [[1, 1, 1], [1, 1, 1]]) ], ids=['float32', 'float16', 'unsigned int8', 'signed int8', 'signed int8']) def test_const_tensor_incorrect_input_datatype(dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) with pytest.raises(TypeError) as err: ann.ConstTensor(tensor_info, data) @@ -163,7 +163,7 @@ def test_const_tensor_incorrect_input_datatype(dt, data): class TestNumpyDataTypes: def test_copy_const_tensor(self, dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) tensor = ann.ConstTensor(tensor_info, data) copied_tensor = ann.ConstTensor(tensor) @@ -175,7 +175,7 @@ class TestNumpyDataTypes: assert copied_tensor.GetDataType() == tensor.GetDataType() def test_const_tensor__str__(self, dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) d_type = tensor_info.GetDataType() num_dimensions = tensor_info.GetNumDimensions() num_bytes = tensor_info.GetNumBytes() @@ -186,7 +186,7 @@ class TestNumpyDataTypes: "{}, NumElements: {}}}".format(d_type, num_bytes, num_dimensions, num_elements) def test_const_tensor_with_info(self, dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) elements = tensor_info.GetNumElements() num_bytes = tensor_info.GetNumBytes() d_type = dt @@ -199,7 +199,7 @@ class TestNumpyDataTypes: assert d_type == tensor.GetDataType() def test_immutable_memory(self, dt, data): - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) tensor = ann.ConstTensor(tensor_info, data) @@ -217,7 +217,7 @@ class TestNumpyDataTypes: ann.DataType_Signed32: np.int32, ann.DataType_Float16: np.float16} - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) tensor = ann.ConstTensor(tensor_info, data) assert np_data_type_mapping[tensor.GetDataType()] == data.dtype @@ -242,10 +242,34 @@ def test_numpy_dtype_mismatch_ann_dtype(dt, data): ann.DataType_Signed32: np.int32, ann.DataType_Float16: np.float16} - tensor_info = _get_tensor_info(dt) + tensor_info = _get_const_tensor_info(dt) with pytest.raises(TypeError) as err: ann.ConstTensor(tensor_info, data) assert str(err.value) == "Expected data to have type {} for type {} but instead got numpy.{}".format( np_data_type_mapping[dt], dt, data.dtype) + +@pytest.mark.parametrize("dt, data", + [ + (ann.DataType_Float32, np.random.randint(1, size=(2, 3)).astype(np.float32)), + (ann.DataType_Float16, np.random.randint(1, size=(2, 3)).astype(np.float16)), + (ann.DataType_QAsymmU8, np.random.randint(1, size=(2, 3)).astype(np.uint8)), + (ann.DataType_QAsymmS8, np.random.randint(1, size=(2, 3)).astype(np.int8)), + (ann.DataType_QSymmS8, np.random.randint(1, size=(2, 3)).astype(np.int8)), + (ann.DataType_Signed32, np.random.randint(1, size=(2, 3)).astype(np.int32)), + (ann.DataType_QSymmS16, np.random.randint(1, size=(2, 3)).astype(np.int16)) + ], ids=['float32', 'float16', 'unsigned int8', 'signed int8', 'signed int8', 'int32', 'int16']) +class TestConstTensorConstructorErrors: + + def test_tensorinfo_isconstant_not_set(self, dt, data): + with pytest.raises(ValueError) as err: + ann.ConstTensor(ann.TensorInfo(ann.TensorShape((2, 2, 3, 3)), dt, 0.0, 0, False), data) + + assert str(err.value) == "TensorInfo when initializing ConstTensor must be set to constant." + + def test_tensor_tensorinfo_isconstant_not_set(self, dt, data): + with pytest.raises(ValueError) as err: + ann.ConstTensor(ann.Tensor(ann.TensorInfo(ann.TensorShape((2, 2, 3, 3)), dt, 0.0, 0, False), data)) + + assert str(err.value) == "TensorInfo of Tensor when initializing ConstTensor must be set to constant." \ No newline at end of file diff --git a/python/pyarmnn/test/test_runtime.py b/python/pyarmnn/test/test_runtime.py index fbdd8044ce..e558e84e28 100644 --- a/python/pyarmnn/test/test_runtime.py +++ b/python/pyarmnn/test/test_runtime.py @@ -27,6 +27,7 @@ def random_runtime(shared_data_folder): input_tensor_id = input_binding_info[0] input_tensor_info = input_binding_info[1] + input_tensor_info.SetConstant() output_names = parser.GetSubgraphOutputTensorNames(graph_id) diff --git a/python/pyarmnn/test/test_tensor_info.py b/python/pyarmnn/test/test_tensor_info.py index dc73533869..e54e2a998c 100644 --- a/python/pyarmnn/test/test_tensor_info.py +++ b/python/pyarmnn/test/test_tensor_info.py @@ -21,7 +21,7 @@ def test_tensor_info_ctor_shape(): def test_tensor_info__str__(): - tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), ann.DataType_QAsymmU8, 0.5, 1) + tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), ann.DataType_QAsymmU8, 0.5, 1, True) assert tensor_info.__str__() == "TensorInfo{DataType: 2, IsQuantized: 1, QuantizationScale: 0.500000, " \ - "QuantizationOffset: 1, NumDimensions: 2, NumElements: 6}" + "QuantizationOffset: 1, IsConstant: 1, NumDimensions: 2, NumElements: 6}" -- cgit v1.2.1