mirror of
https://github.com/MLSysBook/TinyTorch.git
synced 2026-06-03 00:21:14 -05:00
faada251ea
- Update all test files to import from tinytorch.core.* instead of relative paths - Consistent with rock solid foundation principle - Tests now use stable package imports, not local module imports - Ensures tests validate the actual exported package functionality - Aligns with production usage patterns
337 lines
12 KiB
Python
337 lines
12 KiB
Python
"""
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Test suite for the tensor module.
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This tests the student implementations to ensure they work correctly.
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"""
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import pytest
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import numpy as np
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import sys
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import os
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# Import from the main package (rock solid foundation)
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from tinytorch.core.tensor import Tensor
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def safe_numpy(tensor):
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"""Get numpy array from tensor, using .numpy() if available, otherwise .data"""
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if hasattr(tensor, 'numpy'):
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return tensor.numpy()
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else:
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return tensor.data
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def safe_item(tensor):
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"""Get scalar value from tensor, using .item() if available, otherwise .data"""
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if hasattr(tensor, 'item'):
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return tensor.item()
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else:
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return float(tensor.data)
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class TestTensorCreation:
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"""Test tensor creation from different data types."""
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def test_scalar_creation(self):
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"""Test creating tensors from scalars."""
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# Float scalar
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t1 = Tensor(5.0)
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assert t1.shape == ()
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assert t1.size == 1
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assert safe_item(t1) == 5.0
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# Integer scalar
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t2 = Tensor(42)
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assert t2.shape == ()
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assert t2.size == 1
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assert safe_item(t2) == 42.0 # Should convert to float32
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def test_vector_creation(self):
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"""Test creating 1D tensors."""
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t = Tensor([1, 2, 3, 4])
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assert t.shape == (4,)
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assert t.size == 4
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assert t.dtype == np.int32 # Integer list defaults to int32
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np.testing.assert_array_equal(safe_numpy(t), [1, 2, 3, 4])
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def test_matrix_creation(self):
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"""Test creating 2D tensors."""
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t = Tensor([[1, 2], [3, 4]])
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assert t.shape == (2, 2)
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assert t.size == 4
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expected = np.array([[1.0, 2.0], [3.0, 4.0]], dtype='float32')
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np.testing.assert_array_equal(safe_numpy(t), expected)
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def test_numpy_array_creation(self):
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"""Test creating tensors from numpy arrays."""
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arr = np.array([1, 2, 3], dtype='int32')
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t = Tensor(arr)
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assert t.shape == (3,)
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assert t.dtype in ['int32', 'float32'] # May convert
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def test_dtype_specification(self):
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"""Test explicit dtype specification."""
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t = Tensor([1, 2, 3], dtype='int32')
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assert t.dtype == np.int32
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def test_invalid_data_type(self):
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"""Test error handling for invalid data types."""
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with pytest.raises(TypeError):
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Tensor("invalid")
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with pytest.raises(TypeError):
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Tensor({"dict": "invalid"})
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class TestTensorProperties:
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"""Test tensor properties and methods."""
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def test_shape_property(self):
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"""Test shape property for different dimensions."""
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assert Tensor(5).shape == ()
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assert Tensor([1, 2, 3]).shape == (3,)
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assert Tensor([[1, 2], [3, 4]]).shape == (2, 2)
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assert Tensor([[[1]]]).shape == (1, 1, 1)
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def test_size_property(self):
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"""Test size property."""
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assert Tensor(5).size == 1
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assert Tensor([1, 2, 3]).size == 3
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assert Tensor([[1, 2], [3, 4]]).size == 4
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assert Tensor([[[1, 2], [3, 4]], [[5, 6], [7, 8]]]).size == 8
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def test_dtype_property(self):
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"""Test dtype property."""
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t1 = Tensor(5.0)
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assert t1.dtype == np.float32
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t2 = Tensor([1, 2, 3], dtype='int32')
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assert t2.dtype == np.int32
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def test_repr(self):
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"""Test string representation."""
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t = Tensor([1, 2, 3])
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repr_str = repr(t)
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assert 'Tensor' in repr_str
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assert 'shape=' in repr_str
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assert 'dtype=' in repr_str
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class TestArithmeticOperations:
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"""Test tensor arithmetic operations."""
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def test_tensor_addition(self):
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"""Test tensor + tensor addition."""
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a = Tensor([1, 2, 3])
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b = Tensor([4, 5, 6])
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result = a + b
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expected = [5.0, 7.0, 9.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_scalar_addition(self):
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"""Test tensor + scalar addition."""
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a = Tensor([1, 2, 3])
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result = a + 10
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expected = [11.0, 12.0, 13.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_reverse_addition(self):
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"""Test scalar + tensor addition."""
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a = Tensor([1, 2, 3])
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result = 10 + a
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expected = [11.0, 12.0, 13.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_tensor_subtraction(self):
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"""Test tensor - tensor subtraction."""
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a = Tensor([5, 7, 9])
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b = Tensor([1, 2, 3])
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result = a - b
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expected = [4.0, 5.0, 6.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_scalar_subtraction(self):
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"""Test tensor - scalar subtraction."""
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a = Tensor([10, 20, 30])
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result = a - 5
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expected = [5.0, 15.0, 25.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_tensor_multiplication(self):
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"""Test tensor * tensor multiplication."""
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a = Tensor([2, 3, 4])
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b = Tensor([5, 6, 7])
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result = a * b
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expected = [10.0, 18.0, 28.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_scalar_multiplication(self):
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"""Test tensor * scalar multiplication."""
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a = Tensor([1, 2, 3])
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result = a * 3
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expected = [3.0, 6.0, 9.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_reverse_multiplication(self):
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"""Test scalar * tensor multiplication."""
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a = Tensor([1, 2, 3])
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result = 3 * a
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expected = [3.0, 6.0, 9.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_tensor_division(self):
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"""Test tensor / tensor division."""
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a = Tensor([6, 8, 10])
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b = Tensor([2, 4, 5])
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result = a / b
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expected = [3.0, 2.0, 2.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_scalar_division(self):
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"""Test tensor / scalar division."""
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a = Tensor([6, 8, 10])
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result = a / 2
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expected = [3.0, 4.0, 5.0]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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class TestUtilityMethods:
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"""Test tensor utility methods (stretch goals for students)."""
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def test_reshape(self):
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"""Test tensor reshaping (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'reshape'):
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reshaped = t.reshape(4)
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assert reshaped.shape == (4,)
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expected = [1.0, 2.0, 3.0, 4.0]
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np.testing.assert_array_equal(safe_numpy(reshaped), expected)
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# Reshape to 2D
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reshaped2 = t.reshape(1, 4)
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assert reshaped2.shape == (1, 4)
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else:
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pytest.skip("reshape method not implemented - stretch goal for students")
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def test_transpose(self):
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"""Test tensor transpose (if implemented)."""
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t = Tensor([[1, 2, 3], [4, 5, 6]])
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if hasattr(t, 'transpose'):
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transposed = t.transpose()
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assert transposed.shape == (3, 2)
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expected = [[1.0, 4.0], [2.0, 5.0], [3.0, 6.0]]
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np.testing.assert_array_equal(safe_numpy(transposed), expected)
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else:
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pytest.skip("transpose method not implemented - stretch goal for students")
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def test_sum_all(self):
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"""Test summing all elements (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'sum'):
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result = t.sum()
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expected = 10.0
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assert abs(safe_item(result) - expected) < 1e-6
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else:
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pytest.skip("sum method not implemented - stretch goal for students")
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def test_sum_axis(self):
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"""Test summing along specific axes (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'sum'):
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# Sum along axis 0 (columns)
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sum0 = t.sum(axis=0)
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expected0 = [4.0, 6.0]
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np.testing.assert_array_equal(safe_numpy(sum0), expected0)
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# Sum along axis 1 (rows)
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sum1 = t.sum(axis=1)
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expected1 = [3.0, 7.0]
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np.testing.assert_array_equal(safe_numpy(sum1), expected1)
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else:
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pytest.skip("sum method not implemented - stretch goal for students")
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def test_mean(self):
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"""Test mean calculation (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'mean'):
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result = t.mean()
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expected = 2.5
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assert abs(safe_item(result) - expected) < 1e-6
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else:
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pytest.skip("mean method not implemented - stretch goal for students")
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def test_max(self):
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"""Test maximum value (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'max'):
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result = t.max()
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expected = 4.0
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assert abs(safe_item(result) - expected) < 1e-6
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else:
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pytest.skip("max method not implemented - stretch goal for students")
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def test_min(self):
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"""Test minimum value (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'min'):
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result = t.min()
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expected = 1.0
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assert abs(safe_item(result) - expected) < 1e-6
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else:
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pytest.skip("min method not implemented - stretch goal for students")
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def test_item_scalar(self):
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"""Test converting single-element tensor to scalar (if implemented)."""
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t = Tensor(42.0)
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if hasattr(t, 'item'):
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assert t.item() == 42.0
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else:
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pytest.skip("item method not implemented - stretch goal for students")
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def test_item_error(self):
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"""Test item() error for multi-element tensors (if implemented)."""
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t = Tensor([1, 2, 3])
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if hasattr(t, 'item'):
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with pytest.raises(ValueError):
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t.item()
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else:
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pytest.skip("item method not implemented - stretch goal for students")
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def test_numpy_conversion(self):
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"""Test converting tensor to numpy array (if implemented)."""
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t = Tensor([[1, 2], [3, 4]])
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if hasattr(t, 'numpy'):
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arr = t.numpy()
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assert isinstance(arr, np.ndarray)
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expected = [[1.0, 2.0], [3.0, 4.0]]
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np.testing.assert_array_equal(arr, expected)
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else:
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pytest.skip("numpy method not implemented - stretch goal for students")
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class TestEdgeCases:
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"""Test edge cases and error handling."""
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def test_empty_list(self):
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"""Test creating tensor from empty list."""
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t = Tensor([])
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assert t.shape == (0,)
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assert t.size == 0
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def test_mixed_operations(self):
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"""Test combining different operations."""
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a = Tensor([[1, 2], [3, 4]])
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b = Tensor([[2, 2], [2, 2]])
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# Complex expression
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result = (a + b) * 2 - 1
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expected = [[5.0, 7.0], [9.0, 11.0]]
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np.testing.assert_array_equal(safe_numpy(result), expected)
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def test_chained_operations(self):
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"""Test chaining multiple operations (if methods implemented)."""
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t = Tensor([[1, 2, 3], [4, 5, 6]])
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if hasattr(t, 'sum') and hasattr(t, 'mean'):
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result = t.sum(axis=1).mean()
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expected = 10.5 # (6 + 15) / 2
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assert abs(safe_item(result) - expected) < 1e-6
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else:
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pytest.skip("Advanced methods not implemented - stretch goal for students")
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def run_tensor_tests():
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"""Run all tensor tests."""
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pytest.main([__file__, "-v"])
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if __name__ == "__main__":
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run_tensor_tests() |