add oneflow.clone api

oneflow/core/functional/functional_api.yaml

@@ -3145,3 +3145,7 @@
 - name: "mode"
   signature: "TensorTuple[values, indices] (Tensor input, Int32 dim=-1, Bool keepdim=False) => Mode"
   bind_python: True
+
+- name: "clone"
+  signature: "Tensor (Tensor input) => Clone"
+  bind_python: True

oneflow/core/functional/impl/array_functor.cpp

@@ -3918,6 +3918,11 @@ class SortFunctor {
   }
 };
 
+class CloneFunctor {
+ public:
+  Maybe<Tensor> operator()(const std::shared_ptr<Tensor>& input) const { return input->clone(); }
+};
+
 }  // namespace impl
 
 ONEFLOW_FUNCTION_LIBRARY(m) {
@@ -4073,6 +4078,7 @@ ONEFLOW_FUNCTION_LIBRARY(m) {
   m.add_functor<impl::UniqueWithCountsFunctor>("UniqueWithCounts");
   m.add_functor<impl::BaddBmmFunctor>("BaddBmm");
   m.add_functor<impl::SortFunctor>("Sort");
+  m.add_functor<impl::CloneFunctor>("Clone");
 };
 
 }  // namespace functional

python/oneflow/__init__.py

@@ -243,6 +243,7 @@ def is_deprecated(func_or_class):
 from oneflow._C import allclose
 from oneflow._C import index_add, index_add_
 from oneflow._C import sort
+from oneflow._C import clone
 
 from oneflow._oneflow_internal import _set_num_threads as set_num_threads
 

python/oneflow/framework/docstr/array_ops.py

@@ -759,3 +759,30 @@
         tensor([0.0000, 0.2500, 0.2000, 0.0000], dtype=oneflow.float32)
     """,
 )
+
+add_docstr(
+    oneflow.clone,
+    r"""oneflow.clone(input) → Tensor
+
+    Returns a copy of input.
+
+    The documentation is referenced from: https://pytorch.org/docs/1.10/generated/torch.clone.html
+
+    .. note::
+        This function is differentiable, so gradients will flow back from the result
+        of this operation to ``input``. To create a tensor without an autograd relationship
+        to ``input`` see :meth:`detach`.
+
+    Args:
+        input (oneflow.Tensor): input Tensor to be cloned
+
+    For example:
+    .. code-block:: python
+
+        >>> import oneflow as flow
+        >>> x = flow.Tensor([1, 2, 3])
+        >>> y = flow.clone(x)
+        >>> y
+        tensor([1., 2., 3.], dtype=oneflow.float32)
+    """,
+)

python/oneflow/framework/docstr/tensor.py

@@ -2498,3 +2498,19 @@
         tensor([1, 1, 1, 1], dtype=oneflow.int32)
     """,
 )
+
+add_docstr(
+    oneflow.Tensor.clone,
+    """
+    See :func:`oneflow.clone`
+
+    For example:
+
+    .. code-block:: python
+
+        >>> import oneflow as flow
+        >>> x = flow.tensor([1, 2, 3])
+        >>> x.clone()
+        tensor([1, 2, 3], dtype=oneflow.int64)
+    """,
+)

python/oneflow/test/modules/test_clone.py

@@ -0,0 +1,34 @@
+"""
+Copyright 2020 The OneFlow Authors. All rights reserved.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+    http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+"""
+import unittest
+
+import oneflow as flow
+import oneflow.unittest
+
+from oneflow.test_utils.automated_test_util import *
+
+
+@flow.unittest.skip_unless_1n1d()
+class TestClone(flow.unittest.TestCase):
+    @autotest(n=3)
+    def test_clone_with_random_data(test_case):
+        x = random_tensor()
+        y = torch.clone(x)
+        return y
+
+
+if __name__ == "__main__":
+    unittest.main()