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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
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