Add PyArmNN to work with ArmNN API of 20.02
* Add Swig rules for generating python wrapper
* Add documentation
* Add tests and testing data
Change-Id: If48eda08931514fa21e72214dfead2835f07237c
Signed-off-by: Richard Burton <richard.burton@arm.com>
Signed-off-by: Derek Lamberti <derek.lamberti@arm.com>
diff --git a/python/pyarmnn/test/test_tensor.py b/python/pyarmnn/test/test_tensor.py
new file mode 100644
index 0000000..8b57169
--- /dev/null
+++ b/python/pyarmnn/test/test_tensor.py
@@ -0,0 +1,144 @@
+# Copyright © 2020 Arm Ltd. All rights reserved.
+# SPDX-License-Identifier: MIT
+from copy import copy
+
+import pytest
+import numpy as np
+import pyarmnn as ann
+
+
+def __get_tensor_info(dt):
+ tensor_info = ann.TensorInfo(ann.TensorShape((2, 3)), dt)
+
+ return tensor_info
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16,
+ ann.DataType_QAsymmU8, ann.DataType_QSymmS8,
+ ann.DataType_QAsymmS8])
+def test_create_tensor_with_info(dt):
+ tensor_info = __get_tensor_info(dt)
+ elements = tensor_info.GetNumElements()
+ num_bytes = tensor_info.GetNumBytes()
+ d_type = dt
+
+ tensor = ann.Tensor(tensor_info)
+
+ assert tensor_info != tensor.GetInfo(), "Different objects"
+ assert elements == tensor.GetNumElements()
+ assert num_bytes == tensor.GetNumBytes()
+ assert d_type == tensor.GetDataType()
+
+
+def test_create_tensor_undefined_datatype():
+ tensor_info = ann.TensorInfo()
+ tensor_info.SetDataType(99)
+
+ with pytest.raises(ValueError) as err:
+ ann.Tensor(tensor_info)
+
+ assert 'The data type provided for this Tensor is not supported.' in str(err.value)
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float32])
+def test_tensor_memory_output(dt):
+ tensor_info = __get_tensor_info(dt)
+ tensor = ann.Tensor(tensor_info)
+
+ # empty memory area because inference has not yet been run.
+ assert tensor.get_memory_area().tolist() # has random stuff
+ assert 4 == tensor.get_memory_area().itemsize, "it is float32"
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16,
+ ann.DataType_QAsymmU8, ann.DataType_QSymmS8,
+ ann.DataType_QAsymmS8])
+def test_tensor__str__(dt):
+ tensor_info = __get_tensor_info(dt)
+ elements = tensor_info.GetNumElements()
+ num_bytes = tensor_info.GetNumBytes()
+ d_type = dt
+ dimensions = tensor_info.GetNumDimensions()
+
+ tensor = ann.Tensor(tensor_info)
+
+ assert str(tensor) == "Tensor{{DataType: {}, NumBytes: {}, NumDimensions: " \
+ "{}, NumElements: {}}}".format(d_type, num_bytes, dimensions, elements)
+
+
+def test_create_empty_tensor():
+ tensor = ann.Tensor()
+
+ assert 0 == tensor.GetNumElements()
+ assert 0 == tensor.GetNumBytes()
+ assert tensor.get_memory_area() is None
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16,
+ ann.DataType_QAsymmU8, ann.DataType_QSymmS8,
+ ann.DataType_QAsymmS8])
+def test_create_tensor_from_tensor(dt):
+ tensor_info = __get_tensor_info(dt)
+ tensor = ann.Tensor(tensor_info)
+ copied_tensor = ann.Tensor(tensor)
+
+ assert copied_tensor != tensor, "Different objects"
+ assert copied_tensor.GetInfo() != tensor.GetInfo(), "Different objects"
+ assert copied_tensor.get_memory_area().ctypes.data == tensor.get_memory_area().ctypes.data, "Same memory area"
+ assert copied_tensor.GetNumElements() == tensor.GetNumElements()
+ assert copied_tensor.GetNumBytes() == tensor.GetNumBytes()
+ assert copied_tensor.GetDataType() == tensor.GetDataType()
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16,
+ ann.DataType_QAsymmU8, ann.DataType_QSymmS8,
+ ann.DataType_QAsymmS8])
+def test_copy_tensor(dt):
+ tensor = ann.Tensor(__get_tensor_info(dt))
+ copied_tensor = copy(tensor)
+
+ assert copied_tensor != tensor, "Different objects"
+ assert copied_tensor.GetInfo() != tensor.GetInfo(), "Different objects"
+ assert copied_tensor.get_memory_area().ctypes.data == tensor.get_memory_area().ctypes.data, "Same memory area"
+ assert copied_tensor.GetNumElements() == tensor.GetNumElements()
+ assert copied_tensor.GetNumBytes() == tensor.GetNumBytes()
+ assert copied_tensor.GetDataType() == tensor.GetDataType()
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float32, ann.DataType_Float16,
+ ann.DataType_QAsymmU8, ann.DataType_QSymmS8,
+ ann.DataType_QAsymmS8])
+def test_copied_tensor_has_memory_area_access_after_deletion_of_original_tensor(dt):
+
+ tensor = ann.Tensor(__get_tensor_info(dt))
+
+ tensor.get_memory_area()[0] = 100
+
+ initial_mem_copy = np.array(tensor.get_memory_area())
+
+ assert 100 == initial_mem_copy[0]
+
+ copied_tensor = ann.Tensor(tensor)
+
+ del tensor
+ np.testing.assert_array_equal(copied_tensor.get_memory_area(), initial_mem_copy)
+ assert 100 == copied_tensor.get_memory_area()[0]
+
+
+def test_create_const_tensor_incorrect_args():
+ with pytest.raises(ValueError) as err:
+ ann.Tensor('something', 'something')
+
+ expected_error_message = "Incorrect number of arguments or type of arguments provided to create Tensor."
+ assert expected_error_message in str(err.value)
+
+
+@pytest.mark.parametrize("dt", [ann.DataType_Float16])
+def test_tensor_memory_output_fp16(dt):
+ # Check Tensor with float16
+ tensor_info = __get_tensor_info(dt)
+ tensor = ann.Tensor(tensor_info)
+
+ assert tensor.GetNumElements() == 6
+ assert tensor.GetNumBytes() == 12
+ assert tensor.GetDataType() == ann.DataType_Float16