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112 lines
3.1 KiB
Python
112 lines
3.1 KiB
Python
"""
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Test tensor dataclass
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"""
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from dataclasses import dataclass
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from typing import Any
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import pytest
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import torch
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from pyrad.utils.tensor_dataclass import TensorDataclass
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@dataclass
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class TestTensorDataclass(TensorDataclass):
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"""Dummy dataclass"""
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a: torch.Tensor
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b: torch.Tensor
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c: torch.Tensor = None
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def test_init():
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"""Test that dataclass is properly initialized"""
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@dataclass
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class Dummy(TensorDataclass):
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"""Dummy dataclass"""
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dummy_vals: Any = None
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dummy = Dummy(dummy_vals=torch.ones(1))
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with pytest.raises(ValueError):
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dummy = Dummy()
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def test_broadcasting():
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"""Test broadcasting during init"""
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a = torch.ones((4, 6, 3))
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b = torch.ones((6, 2))
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tensor_dataclass = TestTensorDataclass(a=a, b=b)
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assert tensor_dataclass.b.shape == (4, 6, 2)
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a = torch.ones((4, 6, 3))
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b = torch.ones((2))
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tensor_dataclass = TestTensorDataclass(a=a, b=b)
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assert tensor_dataclass.b.shape == (4, 6, 2)
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# Invalid broadcasting
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a = torch.ones((4, 6, 3))
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b = torch.ones((3, 2))
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with pytest.raises(RuntimeError):
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tensor_dataclass = TestTensorDataclass(a=a, b=b)
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def test_tensor_ops():
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"""Test get shape"""
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a = torch.ones((4, 6, 3))
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b = torch.ones((6, 2))
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tensor_dataclass = TestTensorDataclass(a=a, b=b)
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assert tensor_dataclass.shape == (4, 6)
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assert tensor_dataclass.a.shape == (4, 6, 3)
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assert tensor_dataclass.b.shape == (4, 6, 2)
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assert tensor_dataclass.size == 24
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assert tensor_dataclass.ndim == 2
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assert len(tensor_dataclass) == 4
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reshaped = tensor_dataclass.reshape((2, 12))
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assert reshaped.shape == (2, 12)
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assert reshaped.a.shape == (2, 12, 3)
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assert reshaped.b.shape == (2, 12, 2)
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flattened = tensor_dataclass.flatten()
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assert flattened.shape == (24,)
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assert flattened.a.shape == (24, 3)
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assert flattened.b.shape == (24, 2)
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# Test indexing operations
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assert tensor_dataclass[:, 1].shape == (4,)
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assert tensor_dataclass[:, 1].a.shape == (4, 3)
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assert tensor_dataclass[..., 1].shape == (4,)
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assert tensor_dataclass[..., 1].a.shape == (4, 3)
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assert tensor_dataclass[0].shape == (6,)
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assert tensor_dataclass[0].a.shape == (6, 3)
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assert tensor_dataclass[0, ...].shape == (6,)
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assert tensor_dataclass[0, ...].a.shape == (6, 3)
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tensor_dataclass = TestTensorDataclass(a=torch.ones((2, 3, 4, 5)), b=torch.ones((4, 5)))
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assert tensor_dataclass[0, ...].shape == (3, 4)
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assert tensor_dataclass[0, ...].a.shape == (3, 4, 5)
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assert tensor_dataclass[0, ..., 0].shape == (3,)
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assert tensor_dataclass[0, ..., 0].a.shape == (3, 5)
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assert tensor_dataclass[..., 0].shape == (2, 3)
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assert tensor_dataclass[..., 0].a.shape == (2, 3, 5)
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def test_iter():
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"""Test iterating over tensor dataclass"""
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tensor_dataclass = TestTensorDataclass(a=torch.ones((3, 4, 5)), b=torch.ones((3, 4, 5)))
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for batch in tensor_dataclass:
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assert batch.shape == (4,)
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assert batch.a.shape == (4, 5)
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assert batch.b.shape == (4, 5)
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if __name__ == "__main__":
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test_init()
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test_broadcasting()
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test_tensor_ops()
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test_iter()
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