modify flip test=develop (#25312)

According to paddle 2.0 standard
1, change flip api attr name 'dim' to 'axis'.
2, support empty axis
3, change example code to imperative mode.

paddle/fluid/operators/flip_op.cc

@@ -36,46 +36,52 @@ class FlipOp : public framework::OperatorWithKernel {
                       platform::errors::NotFound(
                           "Output(Out) of FlipOp should not be null."));
     auto x_dims = ctx->GetInputDim("X");
-    auto flip_dims = ctx->Attrs().Get<std::vector<int>>("dims");
+    auto flip_dims = ctx->Attrs().Get<std::vector<int>>("axis");
     size_t flip_dims_size = flip_dims.size();
 
-    // check if dims axis within range
-    auto min_max_d = std::minmax_element(flip_dims.begin(), flip_dims.end());
-    PADDLE_ENFORCE_LT(*min_max_d.first, x_dims.size(),
-                      platform::errors::InvalidArgument(
-                          "min(dims) should be less than the input tensor X's "
-                          "dimensions of FlipOp. But received min(dims) = %d,  "
-                          "X's dimensions = %d, X's shape = [%s]",
-                          *min_max_d.first, x_dims.size(), x_dims));
-    PADDLE_ENFORCE_GE(
-        *min_max_d.first, x_dims.size() * -1,
-        platform::errors::InvalidArgument(
-            "min(dims) should be greater than or equal to the input tensor X's "
-            "dimensions of FlipOp times -1. But received min(dims) = %d,  X's "
-            "dimensions = %d, X's shape = [%s]",
-            *min_max_d.first, x_dims.size() * -1, x_dims));
-    PADDLE_ENFORCE_LT(*min_max_d.second, x_dims.size(),
-                      platform::errors::InvalidArgument(
-                          "max(dims) should be less than the input tensor X's "
-                          "dimensions of FlipOp. But received max(dims) = %d,  "
-                          "X's dimensions = %d, X's shape = [%s]",
-                          *min_max_d.second, x_dims.size(), x_dims));
-    PADDLE_ENFORCE_GE(
-        *min_max_d.second, x_dims.size() * -1,
-        platform::errors::InvalidArgument(
-            "max(dims) should be greater than or equal to the input tensor X's "
-            "dimensions of FlipOp times -1. But received max(dims) = %d,  X's "
-            "dimensions = %d, X's shape = [%s]",
-            *min_max_d.second, x_dims.size() * -1, x_dims));
-
-    // check duplicates in dims
-    flip_dims.erase(std::unique(flip_dims.begin(), flip_dims.end()),
-                    flip_dims.end());
-    PADDLE_ENFORCE_EQ(flip_dims.size(), flip_dims_size,
-                      platform::errors::InvalidArgument(
-                          "dims has duplicates, original flip dims size=%d, "
-                          "but unique flip dims size=%d.)",
-                          flip_dims_size, flip_dims.size()));
+    if (flip_dims_size > 0) {
+      // check if dims axis within range
+      auto min_max_d = std::minmax_element(flip_dims.begin(), flip_dims.end());
+      PADDLE_ENFORCE_LT(
+          *min_max_d.first, x_dims.size(),
+          platform::errors::InvalidArgument(
+              "min(axes) should be less than the input tensor X's "
+              "axes of FlipOp. But received min(axes) = %d,  "
+              "X's axes = %d, X's shape = [%s]",
+              *min_max_d.first, x_dims.size(), x_dims));
+      PADDLE_ENFORCE_GE(*min_max_d.first, x_dims.size() * -1,
+                        platform::errors::InvalidArgument(
+                            "min(axes) should be greater than or equal to the "
+                            "input tensor X's "
+                            "axes of FlipOp times -1. But received "
+                            "min(axes) = %d,  X's "
+                            "axes = %d, X's shape = [%s]",
+                            *min_max_d.first, x_dims.size() * -1, x_dims));
+      PADDLE_ENFORCE_LT(
+          *min_max_d.second, x_dims.size(),
+          platform::errors::InvalidArgument(
+              "max(axes) should be less than the input tensor X's "
+              "axes of FlipOp. But received max(axes) = %d,  "
+              "X's axes = %d, X's shape = [%s]",
+              *min_max_d.second, x_dims.size(), x_dims));
+      PADDLE_ENFORCE_GE(*min_max_d.second, x_dims.size() * -1,
+                        platform::errors::InvalidArgument(
+                            "max(axes) should be greater than or equal to the "
+                            "input tensor X's "
+                            "axes of FlipOp times -1. But received "
+                            "max(axes) = %d,  X's "
+                            "axes = %d, X's shape = [%s]",
+                            *min_max_d.second, x_dims.size() * -1, x_dims));
+
+      // check duplicates in dims
+      flip_dims.erase(std::unique(flip_dims.begin(), flip_dims.end()),
+                      flip_dims.end());
+      PADDLE_ENFORCE_EQ(flip_dims.size(), flip_dims_size,
+                        platform::errors::InvalidArgument(
+                            "axes has duplicates, original flip axes size=%d, "
+                            "but unique flip axes size=%d.)",
+                            flip_dims_size, flip_dims.size()));
+    }
 
     VLOG(3) << "flip operator x.shape=" << x_dims;
 
@@ -104,10 +110,10 @@ class FlipOpMaker : public framework::OpProtoAndCheckerMaker {
   void Make() override {
     AddInput("X", "(Tensor), The input tensor of flip op.");
     AddOutput("Out", "(Tensor), The output tensor of flip op.");
-    AddAttr<std::vector<int>>("dims", "The axes to flip on.");
+    AddAttr<std::vector<int>>("axis", "The axes to flip on.");
     AddComment(R"DOC(
           Flip Operator.
-          Reverse the order of a n-D tensor along given axis in dims.
+          Reverse the order of a n-D tensor along given axis in axes.
       )DOC");
   }
 };

paddle/fluid/operators/flip_op.cu

@@ -81,7 +81,7 @@ class FlipKernel<platform::CUDADeviceContext, T>
     Tensor* out = ctx.Output<Tensor>("Out");
     auto* in_data = x->data<T>();
     auto* out_data = out->mutable_data<T>(ctx.GetPlace());
-    auto flip_dims = ctx.template Attr<std::vector<int>>("dims");
+    auto flip_dims = ctx.template Attr<std::vector<int>>("axis");
 
     const int flip_dims_size = static_cast<int>(flip_dims.size());
     auto x_dims = x->dims();

paddle/fluid/operators/flip_op.h

@@ -41,7 +41,7 @@ class FlipKernel<platform::CPUDeviceContext, T>
   void Compute(const framework::ExecutionContext& ctx) const override {
     const Tensor* x = ctx.Input<Tensor>("X");
     Tensor* out = ctx.Output<Tensor>("Out");
-    auto flip_dims = ctx.template Attr<std::vector<int>>("dims");
+    auto flip_dims = ctx.template Attr<std::vector<int>>("axis");
 
     auto x_dims = x->dims();
     const int total_dims = x_dims.size();

python/paddle/__init__.py

@@ -108,7 +108,7 @@
 from .tensor.manipulation import gather  #DEFINE_ALIAS
 from .tensor.manipulation import gather_nd  #DEFINE_ALIAS
 from .tensor.manipulation import reshape  #DEFINE_ALIAS
-from .tensor.manipulation import reverse  #DEFINE_ALIAS
+from .tensor.manipulation import flip as reverse  #DEFINE_ALIAS
 from .tensor.manipulation import scatter  #DEFINE_ALIAS
 from .tensor.manipulation import scatter_nd_add  #DEFINE_ALIAS
 from .tensor.manipulation import scatter_nd  #DEFINE_ALIAS

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

@@ -30,9 +30,9 @@ def test_static_graph(self):
         startup_program = fluid.Program()
         train_program = fluid.Program()
         with fluid.program_guard(train_program, startup_program):
-            dims = [0]
+            axis = [0]
             input = fluid.data(name='input', dtype='float32', shape=[2, 3])
-            output = paddle.flip(input, dims)
+            output = paddle.flip(input, axis)
             place = fluid.CPUPlace()
             if fluid.core.is_compiled_with_cuda():
                 place = fluid.CUDAPlace(0)
@@ -68,7 +68,7 @@ def setUp(self):
         self.outputs = {'Out': self.calc_ref_res()}
 
     def init_attrs(self):
-        self.attrs = {"dims": self.dims}
+        self.attrs = {"axis": self.axis}
 
     def test_check_output(self):
         self.check_output()
@@ -78,37 +78,49 @@ def test_check_grad(self):
 
     def init_test_case(self):
         self.in_shape = (6, 4, 2, 3)
-        self.dims = [0, 1]
+        self.axis = [0, 1]
 
     def calc_ref_res(self):
         res = self.inputs['X']
-        for axis in self.dims:
+        for axis in self.axis:
             res = np.flip(res, axis)
         return res
 
 
 class TestFlipOpAxis1(TestFlipOp):
     def init_test_case(self):
         self.in_shape = (2, 4, 4)
-        self.dims = [0]
+        self.axis = [0]
 
 
 class TestFlipOpAxis2(TestFlipOp):
     def init_test_case(self):
         self.in_shape = (4, 4, 6, 3)
-        self.dims = [0, 2]
+        self.axis = [0, 2]
 
 
 class TestFlipOpAxis3(TestFlipOp):
     def init_test_case(self):
         self.in_shape = (4, 3, 1)
-        self.dims = [0, 1, 2]
+        self.axis = [0, 1, 2]
 
 
 class TestFlipOpAxis4(TestFlipOp):
     def init_test_case(self):
         self.in_shape = (6, 4, 2, 2)
-        self.dims = [0, 1, 2, 3]
+        self.axis = [0, 1, 2, 3]
+
+
+class TestFlipOpEmptyAxis(TestFlipOp):
+    def init_test_case(self):
+        self.in_shape = (6, 4, 2, 2)
+        self.axis = []
+
+
+class TestFlipOpNegAxis(TestFlipOp):
+    def init_test_case(self):
+        self.in_shape = (6, 4, 2, 2)
+        self.axis = [-1]
 
 
 if __name__ == "__main__":

python/paddle/tensor/__init__.py

@@ -81,7 +81,7 @@
 from .manipulation import gather  #DEFINE_ALIAS
 from .manipulation import gather_nd  #DEFINE_ALIAS
 from .manipulation import reshape  #DEFINE_ALIAS
-from .manipulation import reverse  #DEFINE_ALIAS
+from .manipulation import flip as reverse  #DEFINE_ALIAS
 from .manipulation import scatter  #DEFINE_ALIAS
 from .manipulation import scatter_nd_add  #DEFINE_ALIAS
 from .manipulation import scatter_nd  #DEFINE_ALIAS

python/paddle/tensor/manipulation.py

@@ -28,7 +28,6 @@
 from ..fluid.layers import expand_as  #DEFINE_ALIAS
 from ..fluid.layers import flatten  #DEFINE_ALIAS
 from ..fluid.layers import reshape  #DEFINE_ALIAS
-from ..fluid.layers import reverse  #DEFINE_ALIAS
 from ..fluid.layers import scatter  #DEFINE_ALIAS
 from ..fluid.layers import slice  #DEFINE_ALIAS
 from ..fluid.layers import strided_slice  #DEFINE_ALIAS
@@ -51,59 +50,63 @@
 ]
 
 
-def flip(input, dims, name=None):
+def flip(x, axis, name=None):
     """
 	:alias_main: paddle.flip
 	:alias: paddle.flip,paddle.tensor.flip,paddle.tensor.manipulation.flip
 
 
-    Reverse the order of a n-D tensor along given axis in dims.
+    Reverse the order of a n-D tensor along given axis in axis.
 
     Args:
-        input (Variable): A Tensor(or LoDTensor) with shape :math:`[N_1, N_2,..., N_k]` . The data type of the input Tensor
+        x (Variable): A Tensor(or LoDTensor) with shape :math:`[N_1, N_2,..., N_k]` . The data type of the input Tensor x
             should be float32, float64, int32, int64, bool.
-        dims (list): The axis to flip on.
+        axis (list): The axis(axes) to flip on. Negative indices for indexing from the end are accepted.
         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:
-        Variable: Tensor or LoDTensor calculated by flip layer. The data type is same with input.
+        Variable: Tensor or LoDTensor calculated by flip layer. The data type is same with input x.
 
     Examples:
         .. code-block:: python
 
           import paddle
-          import paddle.fluid as fluid
           import numpy as np
-          input = fluid.data(name="x", shape=[-1, 2, 2], dtype='float32')
-          output = paddle.flip(input, dims=[0, 1])
-          exe = fluid.Executor(fluid.CPUPlace())
-          exe.run(fluid.default_startup_program())
-          img = np.arange(12).reshape((3,2,2)).astype(np.float32)
-          res = exe.run(fluid.default_main_program(), feed={'x':img}, fetch_list=[output])
-          print(res) # [[[10,11][8, 9]],[[6, 7],[4, 5]] [[2, 3],[0, 1]]]
+
+          paddle.enable_imperative()
+
+          image_shape=(3, 2, 2)
+          x = np.arange(image_shape[0] * image_shape[1] * image_shape[2]).reshape(image_shape)
+          x = x.astype('float32')
+          img = paddle.imperative.to_variable(x)
+          out = paddle.flip(img, [0,1])
+
+          print(out) # [[[10,11][8, 9]],[[6, 7],[4, 5]] [[2, 3],[0, 1]]]
     """
     helper = LayerHelper("flip", **locals())
-    check_type(input, 'X', (Variable), 'flip')
-    dtype = helper.input_dtype()
+    check_type(x, 'X', (Variable), 'flip')
+    dtype = helper.input_dtype('x')
     check_dtype(dtype, 'X',
                 ['float16', 'float32', 'float64', 'int32', 'int64', 'bool'],
                 'flip')
-    check_type(dims, 'dims', (list, tuple), 'flip')
-    assert len(dims) > 0, 'len(dims) must be greater than 0.'
+    check_type(axis, 'axis', (list, tuple), 'flip')
     if name is None:
         out = helper.create_variable_for_type_inference(dtype)
     else:
         out = helper.create_variable(name=name, dtype=dtype, persistable=False)
 
     helper.append_op(
         type="flip",
-        inputs={"X": input},
+        inputs={"X": x},
         outputs={"Out": out},
-        attrs={"dims": dims})
+        attrs={"axis": axis})
     return out
 
 
+reverse = flip  #DEFINE_ALIAS
+
+
 def roll(x, shifts, axis=None, name=None):
     """
 	:alias_main: paddle.roll