chore: import upstream snapshot with attribution

test/legacy_test/test_diff_op.py

@@ -0,0 +1,456 @@
+#   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.
+
+import unittest
+
+import numpy as np
+from op_test import get_device_place, get_places, is_custom_device
+
+import paddle
+from paddle import static
+
+
+class TestDiffOp(unittest.TestCase):
+    def set_args(self):
+        self.input = np.array([1, 4, 5, 2]).astype('float32')
+        self.n = 1
+        self.axis = -1
+        self.prepend = None
+        self.append = None
+
+    def get_output(self):
+        if self.prepend is not None and self.append is not None:
+            self.output = np.diff(
+                self.input,
+                n=self.n,
+                axis=self.axis,
+                prepend=self.prepend,
+                append=self.append,
+            )
+        elif self.prepend is not None:
+            self.output = np.diff(
+                self.input, n=self.n, axis=self.axis, prepend=self.prepend
+            )
+        elif self.append is not None:
+            self.output = np.diff(
+                self.input, n=self.n, axis=self.axis, append=self.append
+            )
+        else:
+            self.output = np.diff(self.input, n=self.n, axis=self.axis)
+
+    def setUp(self):
+        self.set_args()
+        self.get_output()
+        self.places = get_places()
+
+    def func_dygraph(self):
+        for place in self.places:
+            paddle.disable_static()
+            x = paddle.to_tensor(self.input, place=place)
+            if self.prepend is not None:
+                self.prepend = paddle.to_tensor(self.prepend, place=place)
+            if self.append is not None:
+                self.append = paddle.to_tensor(self.append, place=place)
+            out = paddle.diff(
+                x,
+                n=self.n,
+                axis=self.axis,
+                prepend=self.prepend,
+                append=self.append,
+            )
+            self.assertTrue((out.numpy() == self.output).all(), True)
+
+    def test_dygraph(self):
+        self.setUp()
+        self.func_dygraph()
+
+    def test_static(self):
+        paddle.enable_static()
+        for place in get_places():
+            with paddle.static.program_guard(
+                paddle.static.Program(), paddle.static.Program()
+            ):
+                x = paddle.static.data(
+                    name="input", shape=self.input.shape, dtype=self.input.dtype
+                )
+                has_pend = False
+                prepend = None
+                append = None
+                if self.prepend is not None:
+                    has_pend = True
+                    prepend = paddle.static.data(
+                        name="prepend",
+                        shape=self.prepend.shape,
+                        dtype=self.prepend.dtype,
+                    )
+                if self.append is not None:
+                    has_pend = True
+                    append = paddle.static.data(
+                        name="append",
+                        shape=self.append.shape,
+                        dtype=self.append.dtype,
+                    )
+
+                exe = static.Executor(place)
+                out = paddle.diff(
+                    x, n=self.n, axis=self.axis, prepend=prepend, append=append
+                )
+
+                fetches = exe.run(
+                    feed={
+                        "input": self.input,
+                        "prepend": self.prepend,
+                        "append": self.append,
+                    },
+                    fetch_list=[out],
+                )
+                self.assertTrue((fetches[0] == self.output).all(), True)
+
+    def func_grad(self):
+        for place in self.places:
+            x = paddle.to_tensor(self.input, place=place, stop_gradient=False)
+            if self.prepend is not None:
+                self.prepend = paddle.to_tensor(self.prepend, place=place)
+            if self.append is not None:
+                self.append = paddle.to_tensor(self.append, place=place)
+            out = paddle.diff(
+                x,
+                n=self.n,
+                axis=self.axis,
+                prepend=self.prepend,
+                append=self.append,
+            )
+            try:
+                out.backward()
+                x_grad = x.grad
+            except:
+                raise RuntimeError("Check Diff Gradient Failed")
+
+    def test_grad(self):
+        self.setUp()
+        self.func_grad()
+
+
+class TestDiffOpN(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([1, 4, 5, 2]).astype('float32')
+        self.n = 2
+        self.axis = 0
+        self.prepend = None
+        self.append = None
+
+
+class TestDiffOpNAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = 1
+        self.prepend = None
+        self.append = None
+
+
+class TestDiffOpNPrepend(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = -1
+        self.prepend = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype(
+            'float32'
+        )
+        self.append = None
+
+
+class TestDiffOpNAppend(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = -1
+        self.prepend = None
+        self.append = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype('float32')
+
+
+class TestDiffOpNPreAppend(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = -1
+        self.prepend = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype(
+            'float32'
+        )
+        self.append = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype('float32')
+
+
+class TestDiffOpNPrependAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = 0
+        self.prepend = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype(
+            'float32'
+        )
+        self.append = None
+
+
+class TestDiffOpNAppendAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = 0
+        self.prepend = None
+        self.append = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype('float32')
+
+
+class TestDiffOpNPreAppendAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 2
+        self.axis = 0
+        self.prepend = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype(
+            'float32'
+        )
+        self.append = np.array([[2, 3, 4, 11], [1, 3, 5, 10]]).astype('float32')
+
+
+class TestDiffOpAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = 0
+        self.prepend = None
+        self.append = None
+
+
+class TestDiffOpNDim(TestDiffOp):
+    def set_args(self):
+        self.input = np.random.rand(10, 10).astype('float32')
+        self.n = 1
+        self.axis = -1
+        self.prepend = None
+        self.append = None
+
+
+class TestDiffOpBool(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([0, 1, 1, 0, 1, 0]).astype('bool')
+        self.n = 1
+        self.axis = -1
+        self.prepend = None
+        self.append = None
+
+
+class TestDiffOpPrepend(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = -1
+        self.prepend = np.array([[2, 3, 4], [1, 3, 5]]).astype('float32')
+        self.append = None
+
+
+class TestDiffOpPrependAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = 0
+        self.prepend = np.array(
+            [[0, 2, 3, 4], [1, 3, 5, 7], [2, 5, 8, 0]]
+        ).astype('float32')
+        self.append = None
+
+
+class TestDiffOpAppend(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = -1
+        self.prepend = None
+        self.append = np.array([[2, 3, 4], [1, 3, 5]]).astype('float32')
+
+
+class TestDiffOpAppendAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = 0
+        self.prepend = None
+        self.append = np.array([[2, 3, 4, 1]]).astype('float32')
+
+
+class TestDiffOpPreAppend(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = -1
+        self.prepend = np.array([[0, 4], [5, 9]]).astype('float32')
+        self.append = np.array([[2, 3, 4], [1, 3, 5]]).astype('float32')
+
+
+class TestDiffOpPreAppendAxis(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([[1, 4, 5, 2], [1, 5, 4, 2]]).astype('float32')
+        self.n = 1
+        self.axis = 0
+        self.prepend = np.array([[0, 4, 5, 9], [5, 9, 2, 3]]).astype('float32')
+        self.append = np.array([[2, 3, 4, 7], [1, 3, 5, 6]]).astype('float32')
+
+
+class TestDiffOpFp16(TestDiffOp):
+    def test_fp16_with_gpu(self):
+        paddle.enable_static()
+        if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
+            place = get_device_place()
+            with paddle.static.program_guard(
+                paddle.static.Program(), paddle.static.Program()
+            ):
+                input = np.random.random([4, 4]).astype("float16")
+                x = paddle.static.data(
+                    name="input", shape=[4, 4], dtype="float16"
+                )
+                exe = paddle.static.Executor(place)
+                out = paddle.diff(
+                    x,
+                    n=self.n,
+                    axis=self.axis,
+                    prepend=self.prepend,
+                    append=self.append,
+                )
+                fetches = exe.run(
+                    feed={
+                        "input": input,
+                    },
+                    fetch_list=[out],
+                )
+        paddle.disable_static()
+
+
+class TestDiffOp_ZeroSize(TestDiffOp):
+    def set_args(self):
+        self.input = np.array([1, 0, 5, 2]).astype('float32')
+        self.n = 2
+        self.axis = 0
+        self.prepend = None
+        self.append = None
+
+
+class TestDiffOpFp16_TorchAlias(TestDiffOp):
+    def test_fp16_with_gpu(self):
+        paddle.enable_static()
+        if paddle.base.core.is_compiled_with_cuda() or is_custom_device():
+            place = get_device_place()
+            with paddle.static.program_guard(
+                paddle.static.Program(), paddle.static.Program()
+            ):
+                input = np.random.random([4, 4]).astype("float16")
+                x = paddle.static.data(
+                    name="input", shape=[4, 4], dtype="float16"
+                )
+                exe = paddle.static.Executor(place)
+                out = paddle.diff(
+                    x,
+                    n=self.n,
+                    dim=self.axis,
+                    prepend=self.prepend,
+                    append=self.append,
+                )
+                fetches = exe.run(
+                    feed={
+                        "input": input,
+                    },
+                    fetch_list=[out],
+                )
+        paddle.disable_static()
+
+
+class TestDiffOut(unittest.TestCase):
+    def setUp(self):
+        paddle.disable_static()
+        self.test_configs = [
+            {'shape': [20], 'dtype': 'float32', 'n': 1, 'axis': -1},
+            {'shape': [10, 15], 'dtype': 'float64', 'n': 2, 'axis': 0},
+            {'shape': [6, 8, 10], 'dtype': 'int32', 'n': 3, 'axis': 1},
+            {'shape': [5, 7, 9, 11], 'dtype': 'int64', 'n': 1, 'axis': -1},
+            {
+                'shape': [12, 18],
+                'dtype': 'float64',
+                'n': 1,
+                'axis': 1,
+                'prepend': 3,
+            },
+            {
+                'shape': [8, 10, 12],
+                'dtype': 'int64',
+                'n': 2,
+                'axis': 0,
+                'append': 2,
+            },
+            {
+                'shape': [10, 15],
+                'dtype': 'float32',
+                'n': 1,
+                'axis': -1,
+                'prepend': 2,
+                'append': 2,
+            },
+        ]
+
+    def generate_aux_tensor_np(self, shape, dtype):
+        if 'int' in dtype:
+            return np.random.randint(0, 100, size=shape).astype(dtype)
+        return np.random.randn(*shape).astype(dtype)
+
+    def test_out_parameter(self):
+        for config in self.test_configs:
+            with self.subTest(config=config):
+                shape = config['shape']
+                dtype = config['dtype']
+
+                if 'int' in dtype:
+                    x_np = np.random.randint(0, 100, size=shape).astype(dtype)
+                else:
+                    x_np = np.random.randn(*shape).astype(dtype)
+
+                x_tensor = paddle.to_tensor(x_np)
+
+                paddle_kwargs = {
+                    'n': config.get('n', 1),
+                    'axis': config.get('axis', -1),
+                }
+
+                prepend_size = config.get('prepend')
+                if prepend_size:
+                    p_shape = list(shape)
+                    p_shape[paddle_kwargs['axis']] = prepend_size
+                    prepend_np = self.generate_aux_tensor_np(p_shape, dtype)
+                    paddle_kwargs['prepend'] = paddle.to_tensor(prepend_np)
+
+                append_size = config.get('append')
+                if append_size:
+                    a_shape = list(shape)
+                    a_shape[paddle_kwargs['axis']] = append_size
+                    append_np = self.generate_aux_tensor_np(a_shape, dtype)
+                    paddle_kwargs['append'] = paddle.to_tensor(append_np)
+
+                expected_tensor = paddle.diff(x_tensor, **paddle_kwargs)
+
+                out_tensor = paddle.zeros_like(expected_tensor)
+                paddle.diff(x_tensor, out=out_tensor, **paddle_kwargs)
+
+                np.testing.assert_allclose(
+                    out_tensor.numpy(), expected_tensor.numpy(), rtol=1e-20
+                )
+
+
+if __name__ == '__main__':
+    paddle.enable_static()
+    unittest.main()