dev(hansbug): add ttorch.as_tensor, update constructor of ttorch.Tensor

test/torch/funcs/test_construct.py

@@ -34,6 +34,19 @@ class TestTorchFuncsConstruct:
             }
         })).all()
 
+    @choose_mark()
+    def test_tensor(self):
+        assert ttorch.as_tensor(True) == torch.tensor(True)
+        assert (ttorch.as_tensor([1, 2, 3], dtype=torch.float32) == torch.tensor([1.0, 2.0, 3.0])).all()
+
+        assert (ttorch.as_tensor({
+            'a': torch.tensor([1, 2, 3]),
+            'b': {'x': [[4, 5], [6, 7]]}
+        }, dtype=torch.float32) == ttorch.tensor({
+            'a': [1.0, 2.0, 3.0],
+            'b': {'x': [[4.0, 5.0], [6.0, 7.0]]},
+        })).all()
+
     @choose_mark()
     def test_clone(self):
         t1 = ttorch.clone(torch.tensor([1.0, 2.0, 1.5]))

test/torch/funcs/test_reduction.py

@@ -49,16 +49,16 @@ class TestTorchFuncsReduction:
         assert not r6
 
         r7 = ttorch.all(ttorch.tensor({
-            'a': torch.tensor([True, True, True]),
-            'b': torch.tensor([True, True, False]),
+            'a': [True, True, True],
+            'b': [True, True, False],
         }), reduce=False)
         assert (r7 == ttorch.tensor({
             'a': True, 'b': False
         })).all()
 
         r8 = ttorch.all(ttorch.tensor({
-            'a': torch.tensor([True, True, True]),
-            'b': torch.tensor([True, True, False]),
+            'a': [True, True, True],
+            'b': [True, True, False],
         }), dim=0)
         assert (r8 == ttorch.tensor({
             'a': True, 'b': False
@@ -66,8 +66,8 @@ class TestTorchFuncsReduction:
 
         with pytest.warns(UserWarning):
             r9 = ttorch.all(ttorch.tensor({
-                'a': torch.tensor([True, True, True]),
-                'b': torch.tensor([True, True, False]),
+                'a': [True, True, True],
+                'b': [True, True, False],
             }), dim=0, reduce=True)
         assert (r9 == ttorch.tensor({
             'a': True, 'b': False
@@ -90,41 +90,41 @@ class TestTorchFuncsReduction:
         assert r3 == torch.tensor(False)
         assert not r3
 
-        r4 = ttorch.any({
-            'a': torch.tensor([True, True, True]),
-            'b': torch.tensor([True, True, True]),
-        })
+        r4 = ttorch.any(ttorch.tensor({
+            'a': [True, True, True],
+            'b': [True, True, True],
+        }))
         assert torch.is_tensor(r4)
         assert r4 == torch.tensor(True)
         assert r4
 
-        r5 = ttorch.any({
-            'a': torch.tensor([True, True, True]),
-            'b': torch.tensor([True, True, False]),
-        })
+        r5 = ttorch.any(ttorch.tensor({
+            'a': [True, True, True],
+            'b': [True, True, False],
+        }))
         assert torch.is_tensor(r5)
         assert r5 == torch.tensor(True)
         assert r5
 
-        r6 = ttorch.any({
-            'a': torch.tensor([False, False, False]),
-            'b': torch.tensor([False, False, False]),
-        })
+        r6 = ttorch.any(ttorch.tensor({
+            'a': [False, False, False],
+            'b': [False, False, False],
+        }))
         assert torch.is_tensor(r6)
         assert r6 == torch.tensor(False)
         assert not r6
 
         r7 = ttorch.any(ttorch.tensor({
-            'a': torch.tensor([True, True, False]),
-            'b': torch.tensor([False, False, False]),
+            'a': [True, True, False],
+            'b': [False, False, False],
         }), reduce=False)
         assert (r7 == ttorch.tensor({
             'a': True, 'b': False
         })).all()
 
         r8 = ttorch.any(ttorch.tensor({
-            'a': torch.tensor([True, True, False]),
-            'b': torch.tensor([False, False, False]),
+            'a': [True, True, False],
+            'b': [False, False, False],
         }), dim=0)
         assert (r8 == ttorch.tensor({
             'a': True, 'b': False
@@ -132,8 +132,8 @@ class TestTorchFuncsReduction:
 
         with pytest.warns(UserWarning):
             r9 = ttorch.any(ttorch.tensor({
-                'a': torch.tensor([True, True, False]),
-                'b': torch.tensor([False, False, False]),
+                'a': [True, True, False],
+                'b': [False, False, False],
             }), dim=0, reduce=True)
         assert (r9 == ttorch.tensor({
             'a': True, 'b': False

treetensor/torch/funcs/construct.py

@@ -3,7 +3,7 @@ import torch
 from .base import doc_from_base, func_treelize
 
 __all__ = [
-    'tensor', 'clone',
+    'tensor', 'as_tensor', 'clone',
     'zeros', 'zeros_like',
     'randn', 'randn_like',
     'randint', 'randint_like',
@@ -36,10 +36,36 @@ def tensor(data, *args, **kwargs):
         └── c --> tensor([[ True, False],
                           [False,  True]])
     """
-    if torch.is_tensor(data):
-        return data
-    else:
-        return torch.tensor(data, *args, **kwargs)
+    return torch.tensor(data, *args, **kwargs)
+
+
+@doc_from_base()
+@func_treelize()
+def as_tensor(data, *args, **kwargs):
+    """
+    Convert the data into a :class:`treetensor.torch.Tensor` or :class:`torch.Tensor`.
+
+    Examples::
+
+        >>> import torch
+        >>> import treetensor.torch as ttorch
+        >>> ttorch.as_tensor(True)
+        tensor(True)
+
+        >>> ttorch.as_tensor([1, 2, 3], dtype=torch.float32)
+        tensor([1., 2., 3.])
+
+        >>> ttorch.as_tensor({
+        ...     'a': torch.tensor([1, 2, 3]),
+        ...     'b': {'x': [[4, 5], [6, 7]]}
+        ... }, dtype=torch.float32)
+        <Tensor 0x7fc2b80c25c0>
+        ├── a --> tensor([1., 2., 3.])
+        └── b --> <Tensor 0x7fc2b80c24e0>
+            └── x --> tensor([[4., 5.],
+                              [6., 7.]])
+    """
+    return torch.as_tensor(data, *args, **kwargs)
 
 
 # noinspection PyShadowingBuiltins

treetensor/torch/tensor.py

@@ -18,17 +18,7 @@ doc_from_base = replaceable_partial(original_doc_from_base, base=pytorch.Tensor)
 _TorchProxy, _InstanceTorchProxy = get_tree_proxy(pytorch.Tensor)
 
 
-def _to_tensor(*args, **kwargs):
-    if (len(args) == 1 and not kwargs) or \
-            (not args and set(kwargs.keys()) == {'data'}):
-        data = args[0] if len(args) == 1 else kwargs['data']
-        if isinstance(data, pytorch.Tensor):
-            return data
-
-    return pytorch.tensor(*args, **kwargs)
-
-
-class _BaseTensorMeta(clsmeta(_to_tensor, allow_dict=True)):
+class _BaseTensorMeta(clsmeta(pytorch.as_tensor, allow_dict=True)):
     pass