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diff --git a/python/pyarmnn/test/test_tensor.py b/python/pyarmnn/test/test_tensor.py
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+++ b/python/pyarmnn/test/test_tensor.py
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+# Copyright © 2019 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_QuantisedAsymm8])
+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_QuantisedAsymm8])
+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_QuantisedAsymm8])
+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"
+    np.testing.assert_array_equal(copied_tensor.get_memory_area(), tensor.get_memory_area()), "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_QuantisedAsymm8])
+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"
+    np.testing.assert_array_equal(copied_tensor.get_memory_area(), tensor.get_memory_area()), "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_QuantisedAsymm8])
+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