[New API]add rot90 api (#37634)

* update

* update. test=develop

* fix. test=develop

* fix ut. test=develop

* fix ut. test=develop

* fix ut. test=develop

* update. test=develop

* fix ut. test=develop

* fix ut. test=develop

* fix sample code. test=develop

* fix ut. test=develop

* fix ut. test=develop

* fix ut. test=develop

* fix ut. test=develop

* fix paddle.rot90 doc. test=develop

* update ut. test=develop

* fix. test=develop

* fix .test=develop

* fix .test=develop

* fix doc. test=develop

paddle/fluid/framework/heter_pipeline_trainer_test.cc

@@ -115,8 +115,6 @@ TEST(HeterPipelineTrainerTest, GPU) {
   t3.add_trainers(1);
   t3.add_trainers(1);
   t3.add_trainers(1);
-  t3.add_dump_fields("hello");
-  t3.add_dump_param("fc_0");
   auto* heter_section_param3 = t3.mutable_heter_section_param();
   heter_section_param3->set_num_pipeline_stages(3);
   heter_section_param3->set_pipeline_stage(2);

python/paddle/__init__.py

@@ -150,6 +150,7 @@ from .tensor.manipulation import unsqueeze  # noqa: F401
 from .tensor.manipulation import unsqueeze_  # noqa: F401
 from .tensor.manipulation import unstack  # noqa: F401
 from .tensor.manipulation import flip  # noqa: F401
+from .tensor.manipulation import rot90  # noqa: F401
 from .tensor.manipulation import unbind  # noqa: F401
 from .tensor.manipulation import roll  # noqa: F401
 from .tensor.manipulation import chunk  # noqa: F401
@@ -408,6 +409,7 @@ __all__ = [  # noqa
            'bitwise_not',
            'mm',
            'flip',
+           'rot90',
            'bincount',
            'histogram',
            'multiplex',

python/paddle/fluid/tests/unittests/test_rot90_op.py

+#   Copyright (c) 2021 PaddlePaddle 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.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+import paddle
+import paddle.fluid as fluid
+import paddle.fluid.core as core
+from paddle.fluid import Program, program_guard
+
+
+class TestRot90_API(unittest.TestCase):
+    """Test rot90 api."""
+
+    def test_static_graph(self):
+        paddle.enable_static()
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=1, axes=[0, 1])
+            output = paddle.rot90(output, k=1, axes=[0, 1])
+            output = output.rot90(k=1, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[4, 1], [5, 2], [6, 3]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_static_k_0(self):
+        paddle.enable_static()
+        input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=0, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_static_k_2(self):
+        paddle.enable_static()
+        input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=2, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[6, 5, 4], [3, 2, 1]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_static_k_3(self):
+        paddle.enable_static()
+        input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=3, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[4, 1], [5, 2], [6, 3]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_static_neg_k_1(self):
+        paddle.enable_static()
+        input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=-1, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[4, 1], [5, 2], [6, 3]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_static_neg_k_2(self):
+        paddle.enable_static()
+        input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=-2, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[6, 5, 4], [3, 2, 1]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_static_neg_k_3(self):
+        paddle.enable_static()
+        input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+        startup_program = fluid.Program()
+        train_program = fluid.Program()
+        with fluid.program_guard(train_program, startup_program):
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=-3, axes=[0, 1])
+            place = fluid.CPUPlace()
+            if fluid.core.is_compiled_with_cuda():
+                place = fluid.CUDAPlace(0)
+            exe = fluid.Executor(place)
+            exe.run(startup_program)
+
+            img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+            res = exe.run(train_program,
+                          feed={'input': img},
+                          fetch_list=[output])
+
+            out_np = np.array(res[0])
+            out_ref = np.array([[3, 6], [2, 5], [1, 4]]).astype(np.float32)
+
+            self.assertTrue(
+                (out_np == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(out_np))
+
+    def test_error_api(self):
+        paddle.enable_static()
+
+        ## dims error
+        def run1():
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=1, axes=[0])
+
+        self.assertRaises(ValueError, run1)
+
+        ## input dims error
+        def run2():
+            input = fluid.data(name='input', dtype='float32', shape=[2])
+            output = paddle.rot90(input, k=1, axes=[0, 1])
+
+        self.assertRaises(ValueError, run2)
+
+        def run3():
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=1, axes=[0, 0])
+
+        self.assertRaises(ValueError, run3)
+
+        def run4():
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=1, axes=[3, 1])
+
+        self.assertRaises(ValueError, run4)
+
+        def run5():
+            input = fluid.data(name='input', dtype='float32', shape=[2, 3])
+            output = paddle.rot90(input, k=1, axes=[0, 3])
+
+        self.assertRaises(ValueError, run5)
+
+    def test_dygraph(self):
+        img = np.array([[1, 2, 3], [4, 5, 6]]).astype(np.float32)
+        with fluid.dygraph.guard():
+            inputs = fluid.dygraph.to_variable(img)
+
+            ret = paddle.rot90(inputs, k=1, axes=[0, 1])
+            ret = ret.rot90(1, axes=[0, 1])
+            ret = paddle.rot90(ret, k=1, axes=[0, 1])
+            out_ref = np.array([[4, 1], [5, 2], [6, 3]]).astype(np.float32)
+
+            self.assertTrue(
+                (ret.numpy() == out_ref).all(),
+                msg='rot90 output is wrong, out =' + str(ret.numpy()))
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/tensor/__init__.py

@@ -106,6 +106,7 @@ from .manipulation import unsqueeze  # noqa: F401
 from .manipulation import unsqueeze_  # noqa: F401
 from .manipulation import unstack  # noqa: F401
 from .manipulation import flip  # noqa: F401
+from .manipulation import rot90  # noqa: F401
 from .manipulation import unbind  # noqa: F401
 from .manipulation import roll  # noqa: F401
 from .manipulation import chunk  # noqa: F401
@@ -370,6 +371,7 @@ tensor_method_func  = [ #noqa
            'unsqueeze_',
            'unstack',
            'flip',
+           'rot90',
            'unbind',
            'roll',
            'tile',

python/paddle/tensor/manipulation.py

@@ -495,6 +495,92 @@ def flip(x, axis, name=None):
     return out
 
 
+def rot90(x, k=1, axes=[0, 1], name=None):
+    """
+    Rotate a n-D tensor by 90 degrees in the plane specified by dims axis. Rotation direction is from the first towards the second axis if k > 0, and from the second towards the first for k < 0.
+
+    Args:
+        x (Tensor): The input Tensor(or LoDTensor). The data type of the input Tensor x
+            should be float32, float64, int32, int64, bool.
+        k (int): Number of times to rotate
+        axes (list|tuple): Axis to rotate
+        name (str, optional): The default value is None.  Normally there is no need for user to set this property.
+            For more information, please refer to :ref:`api_guide_Name` .
+
+    Returns:
+        Tensor: Tensor or LoDTensor calculated by rot90 layer. The data type is same with input x.
+
+    Raises:
+        TypeError: If the data type of ``x`` is not Variable
+        TypeError: If the dtype of ``x`` is not float16, float32, float64, int32, int64, bool
+        TypeError: If the data type of ``dims`` is not list, tuple
+
+    Examples:
+        .. code-block:: python
+
+          import paddle
+          import numpy as np
+
+          data = paddle.arange(4)
+          data = paddle.reshape(data, (2, 2))
+          print(data) ## [[0, 1],[2, 3]]
+          y = paddle.rot90(data, 1, [0, 1])
+          print(y) #[[1, 3],[0, 2]]
+          y= paddle.rot90(data, -1, [0, 1])
+          print(y) #[[2, 0],[3, 1]]
+          data2 = paddle.arange(8)
+          data2 = paddle.reshape(data2, (2,2,2))
+          print(data2) ###[[[0, 1],[2, 3]],[[4, 5],[6, 7]]]
+          y = paddle.rot90(data2, 1, [1, 2])
+          print(y)   ### [[[1, 3],[0, 2]],[[5, 7],[4, 6]]]
+    """
+
+    helper = LayerHelper("rot90", **locals())
+    check_type(x, 'X', (Variable), 'rot90')
+    dtype = helper.input_dtype('x')
+    check_dtype(dtype, 'X',
+                ['float16', 'float32', 'float64', 'int32', 'int64', 'bool'],
+                'rot90')
+    check_type(axes, 'axes', (list, tuple), 'rot90')
+
+    input_total_dims = len(x.shape)
+    total_rot_dims = len(axes)
+    if total_rot_dims != 2:
+        raise ValueError("expected total rotation axes == 2, but got axes = {}".
+                         format(total_rot_dims))
+    if input_total_dims < 2:
+        raise ValueError("expected total dims >= 2, but got total dims = {}".
+                         format(input_total_dims))
+
+    if not (axes[0] != axes[1] and abs(axes[0] - axes[1]) != input_total_dims):
+        raise ValueError(
+            "expected rotation axes to be different, but got axis0 = {}, and axis1 = {}".
+            format(axes[0], axes[1]))
+
+    if not (axes[0] < input_total_dims and axes[0] >= -input_total_dims):
+        raise ValueError("Rotation axis0 out of range, axis0 = {}".format(axes[
+            0]))
+    if not (axes[1] < input_total_dims and axes[1] >= -input_total_dims):
+        raise ValueError("Rotation axis1 out of range, axis1 = {}".format(axes[
+            1]))
+
+    ## k % 4
+    k = k % 4 if k >= 0 else 4 - (-k % 4)
+    if k == 0:
+        return x
+    if k == 2:
+        return flip(flip(x, axes[0]), axes[1])
+
+    axes_list = list(range(0, input_total_dims))
+    (axes_list[axes[0]], axes_list[axes[1]]) = (axes_list[axes[1]],
+                                                axes_list[axes[0]])
+    if k == 1:
+        return transpose(flip(x, axes[1]), axes_list)
+    else:
+        # k == 3
+        return flip(transpose(x, axes_list), axes[1])
+
+
 def flatten(x, start_axis=0, stop_axis=-1, name=None):
     r"""
     **Flatten op**