dev(hansbug): upgrade all and any

test/torch/funcs/test_reduction.py

@@ -27,7 +27,7 @@ class TestTorchFuncsReduction:
         r4 = ttorch.all({
             'a': torch.tensor([True, True, True]),
             'b': torch.tensor([True, True, True]),
-        }).all()
+        })
         assert torch.is_tensor(r4)
         assert r4 == torch.tensor(True)
         assert r4
@@ -35,7 +35,7 @@ class TestTorchFuncsReduction:
         r5 = ttorch.all({
             'a': torch.tensor([True, True, True]),
             'b': torch.tensor([True, True, False]),
-        }).all()
+        })
         assert torch.is_tensor(r5)
         assert r5 == torch.tensor(False)
         assert not r5
@@ -43,11 +43,36 @@ class TestTorchFuncsReduction:
         r6 = ttorch.all({
             'a': torch.tensor([False, False, False]),
             'b': torch.tensor([False, False, False]),
-        }).all()
+        })
         assert torch.is_tensor(r6)
         assert r6 == torch.tensor(False)
         assert not r6
 
+        r7 = ttorch.all(ttorch.tensor({
+            'a': torch.tensor([True, True, True]),
+            'b': torch.tensor([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]),
+        }), dim=0)
+        assert (r8 == ttorch.tensor({
+            'a': True, 'b': False
+        })).all()
+
+        with pytest.warns(UserWarning):
+            r9 = ttorch.all(ttorch.tensor({
+                'a': torch.tensor([True, True, True]),
+                'b': torch.tensor([True, True, False]),
+            }), dim=0, reduce=True)
+        assert (r9 == ttorch.tensor({
+            'a': True, 'b': False
+        })).all()
+
     @choose_mark()
     def test_any(self):
         r1 = ttorch.any(torch.tensor([True, True, True]))
@@ -68,7 +93,7 @@ class TestTorchFuncsReduction:
         r4 = ttorch.any({
             'a': torch.tensor([True, True, True]),
             'b': torch.tensor([True, True, True]),
-        }).all()
+        })
         assert torch.is_tensor(r4)
         assert r4 == torch.tensor(True)
         assert r4
@@ -76,7 +101,7 @@ class TestTorchFuncsReduction:
         r5 = ttorch.any({
             'a': torch.tensor([True, True, True]),
             'b': torch.tensor([True, True, False]),
-        }).all()
+        })
         assert torch.is_tensor(r5)
         assert r5 == torch.tensor(True)
         assert r5
@@ -84,11 +109,36 @@ class TestTorchFuncsReduction:
         r6 = ttorch.any({
             'a': torch.tensor([False, False, False]),
             'b': torch.tensor([False, False, False]),
-        }).all()
+        })
         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]),
+        }), 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]),
+        }), dim=0)
+        assert (r8 == ttorch.tensor({
+            'a': True, 'b': False
+        })).all()
+
+        with pytest.warns(UserWarning):
+            r9 = ttorch.any(ttorch.tensor({
+                'a': torch.tensor([True, True, False]),
+                'b': torch.tensor([False, False, False]),
+            }), dim=0, reduce=True)
+        assert (r9 == ttorch.tensor({
+            'a': True, 'b': False
+        })).all()
+
     @choose_mark()
     def test_min(self):
         t1 = ttorch.min(torch.tensor([1.0, 2.0, 1.5]))

test/torch/tensor/test_reduction.py

+import pytest
 import torch
 
 import treetensor.torch as ttorch
@@ -24,6 +25,22 @@ class TestTorchTensorReduction:
         assert t2.dtype == torch.bool
         assert not t2
 
+        t3 = ttorch.tensor({
+            'a': [True, False],
+            'b': {'x': [[True, True, ], [True, True, ]]}
+        }).all(reduce=False)
+        assert (t3 == ttorch.tensor({
+            'a': False, 'b': {'x': True},
+        })).all()
+
+        t4 = ttorch.tensor({
+            'a': [True, False],
+            'b': {'x': [[True, True, ], [True, True, ]]}
+        }).all(dim=0)
+        assert (t4 == ttorch.tensor({
+            'a': False, 'b': {'x': [True, True]},
+        })).all()
+
     @choose_mark()
     def test_any(self):
         t1 = ttorch.Tensor({
@@ -42,6 +59,31 @@ class TestTorchTensorReduction:
         assert t2.dtype == torch.bool
         assert not t2
 
+        t3 = ttorch.Tensor({
+            'a': [True, False],
+            'b': {'x': [[False, False, ], [False, False, ]]}
+        }).any(reduce=False)
+        assert (t3 == ttorch.tensor({
+            'a': True, 'b': False,
+        }))
+
+        t4 = ttorch.Tensor({
+            'a': [True, False],
+            'b': {'x': [[False, False, ], [False, False, ]]}
+        }).any(dim=0)
+        assert (t4 == ttorch.tensor({
+            'a': True, 'b': [False, False],
+        }))
+
+        with pytest.warns(UserWarning):
+            t5 = ttorch.Tensor({
+                'a': [True, False],
+                'b': {'x': [[False, False, ], [False, False, ]]}
+            }).any(dim=0, reduce=True)
+        assert (t5 == ttorch.tensor({
+            'a': True, 'b': [False, False],
+        }))
+
     @choose_mark()
     def test_max(self):
         t1 = ttorch.Tensor({

treetensor/torch/funcs/construct.py

@@ -15,7 +15,7 @@ __all__ = [
 
 @doc_from_base()
 @func_treelize()
-def tensor(*args, **kwargs):
+def tensor(data, *args, **kwargs):
     """
     In ``treetensor``, you can create a tree tensor with simple data structure.
 
@@ -36,7 +36,10 @@ def tensor(*args, **kwargs):
         └── c --> tensor([[ True, False],
                           [False,  True]])
     """
-    return torch.tensor(*args, **kwargs)
+    if torch.is_tensor(data):
+        return data
+    else:
+        return torch.tensor(data, *args, **kwargs)
 
 
 # noinspection PyShadowingBuiltins

treetensor/torch/funcs/reduction.py

@@ -11,11 +11,23 @@ __all__ = [
 ]
 
 
+# noinspection PyShadowingBuiltins,PyUnusedLocal
+@post_reduce(torch.all)
+@func_treelize(return_type=Object)
+def _all_r(input, *args, **kwargs):
+    return input
+
+
 # noinspection PyShadowingBuiltins
+@func_treelize()
+def _all_nr(input, *args, **kwargs):
+    return torch.all(input, *args, **kwargs)
+
+
+# noinspection PyShadowingBuiltins,PyUnusedLocal
 @doc_from_base()
-@rmreduce(torch.all)
-@func_treelize(return_type=Object)
-def all(input, *args, **kwargs):
+@auto_reduce(_all_r, _all_nr)
+def all(input, *args, reduce=None, **kwargs):
     """
     In ``treetensor``, you can get the ``all`` result of a whole tree with this function.
 
@@ -32,29 +44,39 @@ def all(input, *args, **kwargs):
         >>> ttorch.all(ttorch.tensor({'a': [True, True], 'b': {'x': [True, False]}}))
         tensor(False)
 
-    .. note::
-
-        In this ``all`` function, the return value should be a tensor with single boolean value.
-
-        If what you need is a tree of boolean tensors, you should do like this
+        >>> ttorch.all(ttorch.tensor({'a': [True, True], 'b': {'x': [True, False]}}), reduce=False)
+        <Tensor 0x7fcda55652b0>
+        ├── a --> tensor(True)
+        └── b --> <Tensor 0x7fcda5565208>
+            └── x --> tensor(False)
 
-            >>> ttorch.tensor({
-            ...     'a': [True, True],
-            ...     'b': {'x': [True, False]},
-            ... }).map(lambda x: torch.all(x))
-            <Tensor 0x7ff363bbc588>
+        >>> ttorch.all(ttorch.tensor({'a': [True, True], 'b': {'x': [True, False]}}), dim=0)
+        <Tensor 0x7fcda5565780>
         ├── a --> tensor(True)
-            └── b --> <Tensor 0x7ff363bb6438>
+        └── b --> <Tensor 0x7fcda55656d8>
             └── x --> tensor(False)
+
     """
-    return torch.all(input, *args, **kwargs)
+    pass  # pragma: no cover
+
+
+# noinspection PyShadowingBuiltins,PyUnusedLocal
+@post_reduce(torch.any)
+@func_treelize(return_type=Object)
+def _any_r(input, *args, **kwargs):
+    return input
 
 
 # noinspection PyShadowingBuiltins
+@func_treelize()
+def _any_nr(input, *args, **kwargs):
+    return torch.any(input, *args, **kwargs)
+
+
+# noinspection PyShadowingBuiltins,PyUnusedLocal
 @doc_from_base()
-@rmreduce(torch.any)
-@func_treelize(return_type=Object)
-def any(input, *args, **kwargs):
+@auto_reduce(_any_r, _any_nr)
+def any(input, *args, reduce=None, **kwargs):
     """
     In ``treetensor``, you can get the ``any`` result of a whole tree with this function.
 
@@ -86,7 +108,7 @@ def any(input, *args, **kwargs):
             └── b --> <Tensor 0x7ff363bc67f0>
                 └── x --> tensor(False)
     """
-    return torch.any(input, *args, **kwargs)
+    pass  # pragma: no cover
 
 
 # noinspection PyShadowingBuiltins

treetensor/torch/tensor.py

@@ -184,25 +184,45 @@ class Tensor(Torch, metaclass=clsmeta(_to_tensor, allow_dict=True)):
         """
         return self.requires_grad_(requires_grad)
 
+    # noinspection PyShadowingBuiltins,PyUnusedLocal
+    @post_reduce(torch.all)
+    @method_treelize(return_type=Object)
+    def __all_r(self, *args, **kwargs):
+        return self
+
+    # noinspection PyShadowingBuiltins
+    @method_treelize()
+    def __all_nr(self, *args, **kwargs):
+        return torch.all(self, *args, **kwargs)
+
     # noinspection PyArgumentList
     @doc_from_base()
-    @rmreduce(torch.all)
-    @method_treelize(return_type=Object)
-    def all(self: torch.Tensor, *args, **kwargs) -> bool:
+    @auto_reduce(__all_r, __all_nr)
+    def all(self: torch.Tensor, *args, reduce=None, **kwargs) -> bool:
         """
         See :func:`treetensor.torch.all`
         """
-        return self.all(*args, **kwargs)
+        pass  # pragma: no cover
+
+    # noinspection PyShadowingBuiltins,PyUnusedLocal
+    @post_reduce(torch.any)
+    @method_treelize(return_type=Object)
+    def __any_r(self, *args, **kwargs):
+        return self
+
+    # noinspection PyShadowingBuiltins
+    @method_treelize()
+    def __any_nr(self, *args, **kwargs):
+        return torch.any(self, *args, **kwargs)
 
     # noinspection PyArgumentList
     @doc_from_base()
-    @rmreduce(torch.any)
-    @method_treelize(return_type=Object)
-    def any(self: torch.Tensor, *args, **kwargs) -> bool:
+    @auto_reduce(__any_r, __any_nr)
+    def any(self: torch.Tensor, *args, reduce=None, **kwargs) -> bool:
         """
         See :func:`treetensor.torch.any`
         """
-        return self.any(*args, **kwargs)
+        pass  # pragma: no cover
 
     @doc_from_base()
     @rmreduce(torch.max)
@@ -762,7 +782,7 @@ class Tensor(Torch, metaclass=clsmeta(_to_tensor, allow_dict=True)):
     @doc_from_base()
     @auto_reduce(__std_r, __std_nr)
     @method_treelize()
-    def std(self, *args, **kwargs):
+    def std(self, *args, reduce=None, **kwargs):
         """
         See :func:`treetensor.torch.std`.
         """
@@ -781,7 +801,7 @@ class Tensor(Torch, metaclass=clsmeta(_to_tensor, allow_dict=True)):
     @doc_from_base()
     @auto_reduce(__mean_r, __mean_nr)
     @method_treelize()
-    def mean(self, *args, **kwargs):
+    def mean(self, *args, reduce=None, **kwargs):
         """
         See :func:`treetensor.torch.mean`.
         """