Multiplication and Division Testing

tests/test_muldiv.py

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+import random
+
+import numpy as np
+import pytest
+
+import arrayfire_wrapper.dtypes as dtype
+import arrayfire_wrapper.lib as wrapper
+from tests.utility_functions import check_type_supported, get_all_types
+
+
+@pytest.mark.parametrize(
+    "shape",
+    [
+        (),
+        (random.randint(1, 10),),
+        (random.randint(1, 10), random.randint(1, 10)),
+        (random.randint(1, 10), random.randint(1, 10), random.randint(1, 10)),
+        (random.randint(1, 10), random.randint(1, 10), random.randint(1, 10), random.randint(1, 10)),
+    ],
+)
+def test_multiply_shapes(shape: tuple) -> None:
+    """Test multiplication operation between two arrays of the same shape"""
+    lhs = wrapper.randu(shape, dtype.f16)
+    rhs = wrapper.randu(shape, dtype.f16)
+
+    result = wrapper.mul(lhs, rhs)
+
+    assert wrapper.get_dims(result)[0 : len(shape)] == shape  # noqa
+
+
+def test_multiply_different_shapes() -> None:
+    """Test if multiplication handles arrays of different shapes"""
+    with pytest.raises(RuntimeError):
+        lhs_shape = (2, 3)
+        rhs_shape = (3, 2)
+        dtypes = dtype.f16
+        lhs = wrapper.randu(lhs_shape, dtypes)
+        rhs = wrapper.randu(rhs_shape, dtypes)
+        result = wrapper.mul(lhs, rhs)
+        assert (
+            wrapper.get_dims(result)[0 : len(lhs_shape)] == lhs_shape  # noqa
+        ), f"Failed for shapes {lhs_shape} and {rhs_shape}"
+
+
+def test_multiply_negative_shapes() -> None:
+    """Test if multiplication handles arrays of negative shapes"""
+    with pytest.raises(RuntimeError):
+        lhs_shape = (2, -2)
+        rhs_shape = (-2, 2)
+        dtypes = dtype.f16
+        lhs = wrapper.randu(lhs_shape, dtypes)
+        rhs = wrapper.randu(rhs_shape, dtypes)
+        result = wrapper.mul(lhs, rhs)
+        assert (
+            wrapper.get_dims(result)[0 : len(lhs_shape)] == lhs_shape  # noqa
+        ), f"Failed for shapes {lhs_shape} and {rhs_shape}"
+
+
+@pytest.mark.parametrize("dtype_name", get_all_types())
+def test_multiply_supported_dtypes(dtype_name: dtype.Dtype) -> None:
+    """Test multiplication operation across all supported data types."""
+    check_type_supported(dtype_name)
+    shape = (5, 5)
+    lhs = wrapper.randu(shape, dtype_name)
+    rhs = wrapper.randu(shape, dtype_name)
+    result = wrapper.mul(lhs, rhs)
+    assert dtype.c_api_value_to_dtype(wrapper.get_type(result)) == dtype_name, f"Failed for dtype: {dtype_name}"
+
+
+@pytest.mark.parametrize(
+    "invdtypes",
+    [
+        dtype.c64,
+        dtype.f64,
+    ],
+)
+def test_multiply_unsupported_dtypes(invdtypes: dtype.Dtype) -> None:
+    """Test multiplication operation for unsupported data types."""
+    with pytest.raises(RuntimeError):
+        shape = (5, 5)
+        lhs = wrapper.randu(shape, invdtypes)
+        rhs = wrapper.randu(shape, invdtypes)
+        wrapper.mul(lhs, rhs)
+
+
+def test_multiply_zero_sized_arrays() -> None:
+    """Test multiplication with arrays where at least one array has zero size."""
+    with pytest.raises(RuntimeError):
+        zero_shape = (0, 5)
+        normal_shape = (5, 5)
+        zero_array = wrapper.randu(zero_shape, dtype.f32)
+        normal_array = wrapper.randu(normal_shape, dtype.f32)
+
+        result_rhs_zero = wrapper.mul(normal_array, zero_array)
+        assert wrapper.get_dims(result_rhs_zero) == normal_shape
+
+        result_lhs_zero = wrapper.mul(zero_array, normal_array)
+        assert wrapper.get_dims(result_lhs_zero) == zero_shape
+
+
+@pytest.mark.parametrize(
+    "shape_a, shape_b",
+    [
+        ((1, 5), (5, 1)),  # 2D with 2D inverse
+        ((5, 5), (5, 1)),  # 2D with 2D
+        ((5, 5), (1, 1)),  # 2D with 2D
+        ((1, 1, 1), (5, 5, 5)),  # 3D with 3D
+        ((5,), (5,)),  # 1D with 1D broadcast
+    ],
+)
+def test_multiply_varying_dimensionality(shape_a: tuple, shape_b: tuple) -> None:
+    """Test multiplication with arrays of varying dimensionality."""
+    lhs = wrapper.randu(shape_a, dtype.f32)
+    rhs = wrapper.randu(shape_b, dtype.f32)
+
+    result = wrapper.mul(lhs, rhs)
+    expected_shape = np.broadcast(np.empty(shape_a), np.empty(shape_b)).shape
+    assert (
+        wrapper.get_dims(result)[0 : len(expected_shape)] == expected_shape  # noqa
+    ), f"Failed for shapes {shape_a} and {shape_b}"
+
+
+@pytest.mark.parametrize(
+    "shape",
+    [
+        (),
+        (random.randint(1, 10),),
+        (random.randint(1, 10), random.randint(1, 10)),
+        (random.randint(1, 10), random.randint(1, 10), random.randint(1, 10)),
+        (random.randint(1, 10), random.randint(1, 10), random.randint(1, 10), random.randint(1, 10)),
+    ],
+)
+def test_divide_shapes(shape: tuple) -> None:
+    """Test division operation between two arrays of the same shape"""
+    lhs = wrapper.randu(shape, dtype.f16)
+    rhs = wrapper.randu(shape, dtype.f16)
+    rhs = wrapper.add(rhs, wrapper.constant(0.001, shape, dtype.f16))
+
+    result = wrapper.div(lhs, rhs)
+
+    assert wrapper.get_dims(result)[0 : len(shape)] == shape  # noqa
+
+
+def test_divide_different_shapes() -> None:
+    """Test if division handles arrays of different shapes"""
+    with pytest.raises(RuntimeError):
+        lhs_shape = (2, 3)
+        rhs_shape = (3, 2)
+        dtypes = dtype.f16
+        lhs = wrapper.randu(lhs_shape, dtypes)
+        rhs = wrapper.randu(rhs_shape, dtypes)
+        result = wrapper.div(lhs, rhs)
+        expected_shape = np.broadcast(np.empty(lhs_shape), np.empty(rhs_shape)).shape
+        assert (
+            wrapper.get_dims(result)[0 : len(expected_shape)] == expected_shape  # noqa
+        ), f"Failed for shapes {lhs_shape} and {rhs_shape}"
+
+
+def test_divide_negative_shapes() -> None:
+    """Test if division handles arrays of negative shapes"""
+    with pytest.raises(RuntimeError):
+        lhs_shape = (2, -2)
+        rhs_shape = (-2, 2)
+        dtypes = dtype.f16
+        lhs = wrapper.randu(lhs_shape, dtypes)
+        rhs = wrapper.randu(rhs_shape, dtypes)
+        result = wrapper.div(lhs, rhs)
+        expected_shape = np.broadcast(np.empty(lhs_shape), np.empty(rhs_shape)).shape
+        assert (
+            wrapper.get_dims(result)[0 : len(expected_shape)] == expected_shape  # noqa
+        ), f"Failed for shapes {lhs_shape} and {rhs_shape}"
+
+
+@pytest.mark.parametrize("dtype_name", get_all_types())
+def test_divide_supported_dtypes(dtype_name: dtype.Dtype) -> None:
+    """Test division operation across all supported data types."""
+    check_type_supported(dtype_name)
+    shape = (5, 5)
+    lhs = wrapper.randu(shape, dtype_name)
+    rhs = wrapper.randu(shape, dtype_name)
+    rhs = wrapper.add(rhs, wrapper.constant(0.001, shape, dtype_name))
+
+    result = wrapper.div(lhs, rhs)
+    assert dtype.c_api_value_to_dtype(wrapper.get_type(result)) == dtype_name, f"Failed for dtype: {dtype_name}"
+
+
+@pytest.mark.parametrize(
+    "invdtypes",
+    [
+        dtype.c64,
+        dtype.f64,
+    ],
+)
+def test_divide_unsupported_dtypes(invdtypes: dtype.Dtype) -> None:
+    """Test division operation for unsupported data types."""
+    with pytest.raises(RuntimeError):
+        shape = (5, 5)
+        lhs = wrapper.randu(shape, invdtypes)
+        rhs = wrapper.randu(shape, invdtypes)
+        # Prevent division by zero in unsupported dtype test
+        rhs = wrapper.add(rhs, wrapper.constant(0.001, shape, invdtypes))
+
+        wrapper.div(lhs, rhs)
+
+
+def test_divide_zero_sized_arrays() -> None:
+    """Test division with arrays where at least one array has zero size."""
+    with pytest.raises(RuntimeError):
+        zero_shape = (0, 5)
+        normal_shape = (5, 5)
+        zero_array = wrapper.randu(zero_shape, dtype.f32)
+        normal_array = wrapper.randu(normal_shape, dtype.f32)
+
+        result_rhs_zero = wrapper.div(normal_array, zero_array)
+        assert wrapper.get_dims(result_rhs_zero) == normal_shape
+
+        result_lhs_zero = wrapper.div(zero_array, normal_array)
+        assert wrapper.get_dims(result_lhs_zero) == zero_shape
+
+
+@pytest.mark.parametrize(
+    "shape_a, shape_b",
+    [
+        ((1, 5), (5, 1)),  # 2D with 2D inverse
+        ((5, 5), (5, 1)),  # 2D with 2D
+        ((5, 5), (1, 1)),  # 2D with 2D
+        ((1, 1, 1), (5, 5, 5)),  # 3D with 3D
+        ((5,), (5,)),  # 1D with 1D broadcast
+    ],
+)
+def test_divide_varying_dimensionality(shape_a: tuple, shape_b: tuple) -> None:
+    """Test division with arrays of varying dimensionality."""
+    lhs = wrapper.randu(shape_a, dtype.f32)
+    rhs = wrapper.randu(shape_b, dtype.f32)
+    # Prevent division by zero for dimensional test
+    rhs = wrapper.add(rhs, wrapper.constant(0.001, shape_b, dtype.f32))
+
+    result = wrapper.div(lhs, rhs)
+    expected_shape = np.broadcast(np.empty(shape_a), np.empty(shape_b)).shape
+    assert (
+        wrapper.get_dims(result)[0 : len(expected_shape)] == expected_shape  # noqa
+    ), f"Failed for shapes {shape_a} and {shape_b}"