Add isclose op (#37135)

* add isclose op, test=develop

* add isclose op, test=develop

* add isclose api, test=develop

* rm useless code

* rm useless code

* update python api of isclose

* add some unittest of isclose op, test=develop

paddle/fluid/operators/isclose_op.cc

+// 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.
+
+#include "paddle/fluid/operators/isclose_op.h"
+#include <cmath>
+#include <string>
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/op_version_registry.h"
+#include "paddle/fluid/framework/operator.h"
+#include "paddle/fluid/platform/enforce.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+struct GetTensorValue<platform::CPUDeviceContext, T> {
+  T operator()(const platform::CPUDeviceContext& dev_ctx,
+               const framework::Tensor& tensor) const {
+    return *(tensor.data<T>());
+  }
+};
+
+template <typename T>
+struct IscloseFunctor<platform::CPUDeviceContext, T> {
+  void operator()(const platform::CPUDeviceContext& ctx,
+                  const framework::Tensor& in, const framework::Tensor& other,
+                  const double rtol, const double atol, bool equal_nan,
+                  framework::Tensor* output) {
+    auto* in_a = in.data<T>();
+    auto* in_b = other.data<T>();
+    auto* out_data = output->mutable_data<bool>(ctx.GetPlace());
+    auto num = in.numel();
+    // *out_data = true;
+    for (int i = 0; i < num; i++) {
+      out_data[i] = true;
+    }
+    for (int i = 0; i < num; i++) {
+      const T a = in_a[i], b = in_b[i];
+      bool val;
+      if (std::isnan(a) || std::isnan(b)) {
+        val = equal_nan && std::isnan(a) == std::isnan(b);
+      } else {
+        T left = (a > b ? a - b : b - a);
+        T right = atol + (b > 0 ? rtol * b : (-rtol) * b);
+        T diff = (left > right ? left - right : right - left);
+        val = a == b || left <= right || diff <= 1e-15;
+      }
+      // *out_data &= val;
+      out_data[i] = val;
+    }
+  }
+};
+
+class IscloseOpMaker : public framework::OpProtoAndCheckerMaker {
+ public:
+  void Make() override {
+    AddInput("Input",
+             "The input tensor, it's data type should be float32, float64.");
+    AddInput("Other",
+             "The input tensor, it's data type should be float32, float64.");
+    AddInput("Rtol", "The relative tolerance.").AsDispensable();
+    AddInput("Atol", "The absolute tolerance.").AsDispensable();
+    AddOutput("Out", "The output tensor, it's data type is bool.");
+    AddAttr<std::string>("rtol",
+                         "The relative tolerance. Default: :math:`1e-5` .")
+        .SetDefault("1e-5");
+    AddAttr<std::string>("atol",
+                         "The absolute tolerance. Default: :math:`1e-8` .")
+        .SetDefault("1e-8");
+    AddAttr<bool>("equal_nan",
+                  "If :math:`True` , then two :math:`NaNs` will be "
+                  "compared as equal. Default: :math:`False` .")
+        .SetDefault(false);
+
+    AddComment(R"DOC( 
+This operator checks if all :math:`x` and :math:`y` satisfy the condition:
+
+.. math::
+    \left| x - y \right| \leq atol + rtol \times \left| y \right|
+
+elementwise, for all elements of :math:`x` and :math:`y`. The behaviour of this
+operator is analogous to :math:`numpy.isclose`, namely that it returns :math:`True` if
+two tensors are elementwise equal within a tolerance.
+)DOC");
+  }
+};
+
+class IscloseOp : public framework::OperatorWithKernel {
+ public:
+  using framework::OperatorWithKernel::OperatorWithKernel;
+
+  void InferShape(framework::InferShapeContext* ctx) const override {
+    OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "Isclose");
+    OP_INOUT_CHECK(ctx->HasInput("Other"), "Input", "Other", "Isclose");
+    OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Isclose");
+
+    auto input_dim = ctx->GetInputDim("Input");
+    auto other_dim = ctx->GetInputDim("Other");
+    PADDLE_ENFORCE_EQ(input_dim.size(), other_dim.size(),
+                      platform::errors::PreconditionNotMet(
+                          "Input(Input) and Input(Other) must have the same "
+                          "dimension size."));
+    int n = input_dim.size();
+    bool is_runtime = ctx->IsRuntime();
+    for (int i = 0; i < n; i++) {
+      if (is_runtime) {
+        PADDLE_ENFORCE_EQ(input_dim[i], other_dim[i],
+                          platform::errors::PreconditionNotMet(
+                              "The value at dim %d of Input(Input) is not "
+                              "equal to the Input(Other): %ld != %ld.",
+                              i, input_dim[i], other_dim[i]));
+      } else {
+        if (!(input_dim[i] < 0 || other_dim[i] < 0)) {
+          PADDLE_ENFORCE_EQ(input_dim[i], other_dim[i],
+                            platform::errors::PreconditionNotMet(
+                                "The value at dim %d of Input(Input) is not "
+                                "equal to the Input(Other): %ld != %ld.",
+                                i, input_dim[i], other_dim[i]));
+        }
+      }
+    }
+
+    ctx->SetOutputDim("Out", input_dim);
+  }
+
+ protected:
+  framework::OpKernelType GetExpectedKernelType(
+      const framework::ExecutionContext& ctx) const override {
+    return framework::OpKernelType(
+        OperatorWithKernel::IndicateVarDataType(ctx, "Input"),
+        ctx.device_context());
+  }
+};
+
+class IscloseOpVarTypeInference : public framework::VarTypeInference {
+ public:
+  void operator()(framework::InferVarTypeContext* ctx) const override {
+    ctx->SetOutputDataType("Out", framework::proto::VarType::BOOL);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+using CPU = paddle::platform::CPUDeviceContext;
+
+REGISTER_OPERATOR(
+    isclose, ops::IscloseOp, ops::IscloseOpMaker,
+    paddle::framework::EmptyGradOpMaker<paddle::framework::OpDesc>,
+    paddle::framework::EmptyGradOpMaker<paddle::imperative::OpBase>,
+    ops::IscloseOpVarTypeInference);
+REGISTER_OP_CPU_KERNEL(isclose, ops::IscloseKernel<CPU, float>,
+                       ops::IscloseKernel<CPU, double>);

paddle/fluid/operators/isclose_op.cu

+// 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.
+
+#include "paddle/fluid/framework/op_registry.h"
+#include "paddle/fluid/framework/operator.h"
+#include "paddle/fluid/operators/isclose_op.h"
+
+namespace paddle {
+namespace operators {
+
+template <typename T>
+struct GetTensorValue<platform::CUDADeviceContext, T> {
+  T operator()(const platform::CUDADeviceContext& dev_ctx,
+               const framework::Tensor& tensor) const {
+    const T* data = tensor.data<T>();
+    T value;
+    const auto gpu_place =
+        BOOST_GET_CONST(platform::CUDAPlace, dev_ctx.GetPlace());
+    memory::Copy(platform::CPUPlace(), &value, gpu_place, data, sizeof(T),
+                 dev_ctx.stream());
+    return value;
+  }
+};
+
+template <typename T>
+__global__ void IscloseCUDAKernel(const T* in_data, const T* other_data,
+                                  const double rtol, const double atol,
+                                  bool equal_nan, int num, bool* out_data) {
+  unsigned int idx = threadIdx.x + blockIdx.x * blockDim.x;
+  bool val;
+  for (int i = idx; i < num; i += blockDim.x * gridDim.x) {
+    const T a = in_data[i], b = other_data[i];
+    if (isnan(a) || isnan(b)) {
+      val = equal_nan && isnan(a) == isnan(b);
+    } else {
+      T left = (a > b ? a - b : b - a);
+      T right = atol + (b > 0 ? rtol * b : (-rtol) * b);
+      T diff = (left > right ? left - right : right - left);
+      val = a == b || left <= right || diff <= 1e-15;
+    }
+    out_data[i] = val;
+    // if (!val) *out_data = false;
+  }
+}
+
+template <typename T>
+struct IscloseFunctor<platform::CUDADeviceContext, T> {
+  void operator()(const platform::CUDADeviceContext& dev_ctx,
+                  const framework::Tensor& in, const framework::Tensor& other,
+                  const double rtol, const double atol, bool equal_nan,
+                  framework::Tensor* output) {
+    int num = in.numel();
+    const T* in_data = in.data<T>();
+    const T* other_data = other.data<T>();
+    bool* out_data = output->mutable_data<bool>(dev_ctx.GetPlace());
+    int block = 1024;
+    int grid = (block - 1 + num) / block;
+    grid = (grid > block) ? block : grid;
+#ifdef PADDLE_WITH_HIP
+    hipMemset(out_data, true, num * sizeof(bool));
+#else
+    cudaMemset(out_data, true, num * sizeof(bool));
+#endif
+    IscloseCUDAKernel<T><<<grid, block, 0, dev_ctx.stream()>>>(
+        in_data, other_data, rtol, atol, equal_nan, num, out_data);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle
+
+namespace ops = paddle::operators;
+using CUDA = paddle::platform::CUDADeviceContext;
+REGISTER_OP_CUDA_KERNEL(isclose, ops::IscloseKernel<CUDA, float>,
+                        ops::IscloseKernel<CUDA, double>);

paddle/fluid/operators/isclose_op.h

+// 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.
+
+#pragma once
+
+#include <string>
+#include "paddle/fluid/framework/data_type.h"
+#include "paddle/fluid/framework/eigen.h"
+#include "paddle/fluid/framework/operator.h"
+#include "paddle/fluid/platform/place.h"
+
+namespace paddle {
+namespace operators {
+using Tensor = framework::Tensor;
+
+template <typename DeviceContext, typename T>
+struct GetTensorValue {
+  T operator()(const platform::DeviceContext& ctx,
+               const framework::Tensor& tensor) const;
+};
+
+template <typename DeviceContext, typename T>
+struct IscloseFunctor {
+  void operator()(const DeviceContext& ctx, const framework::Tensor& in,
+                  const framework::Tensor& other, const float rtol,
+                  const float atol, bool equal_nan, framework::Tensor* output);
+};
+
+template <typename DeviceContext, typename T>
+class IscloseKernel : public framework::OpKernel<T> {
+ public:
+  void Compute(const framework::ExecutionContext& ctx) const override {
+    // get attrs
+    bool equal_nan = ctx.Attr<bool>("equal_nan");
+    // get input/output
+    const auto* input = ctx.Input<Tensor>("Input");
+    const auto* other = ctx.Input<Tensor>("Other");
+    auto* out = ctx.Output<Tensor>("Out");
+
+    double rtol_v = std::stod(ctx.Attr<std::string>("rtol"));
+    double atol_v = std::stod(ctx.Attr<std::string>("atol"));
+
+    auto& dev_ctx = ctx.template device_context<DeviceContext>();
+    GetTensorValue<DeviceContext, double> get_tensor_value;
+    if (ctx.HasInput("Rtol")) {
+      const auto* rtol = ctx.Input<Tensor>("Rtol");
+      PADDLE_ENFORCE_EQ(
+          rtol->numel(), 1,
+          platform::errors::InvalidArgument(
+              "Input(Rtol) size must be 1, but get %d.", rtol->numel()));
+      PADDLE_ENFORCE_EQ(rtol->type(), framework::proto::VarType::FP64,
+                        platform::errors::InvalidArgument(
+                            "Input(Rtol) type must be double, but get %s.",
+                            framework::DataTypeToString(rtol->type())));
+      rtol_v = get_tensor_value(dev_ctx, *rtol);
+    }
+    if (ctx.HasInput("Atol")) {
+      const auto* atol = ctx.Input<Tensor>("Atol");
+      PADDLE_ENFORCE_EQ(
+          atol->numel(), 1,
+          platform::errors::InvalidArgument(
+              "Input(Atol) size must be 1, but get %d", atol->numel()));
+      PADDLE_ENFORCE_EQ(atol->type(), framework::proto::VarType::FP64,
+                        platform::errors::InvalidArgument(
+                            "Input(Atol) type must be double, but get %s",
+                            framework::DataTypeToString(atol->type())));
+      atol_v = get_tensor_value(dev_ctx, *atol);
+    }
+
+    IscloseFunctor<DeviceContext, T>()(dev_ctx, *input, *other, rtol_v, atol_v,
+                                       equal_nan, out);
+  }
+};
+
+}  // namespace operators
+}  // namespace paddle

python/paddle/__init__.py

@@ -117,6 +117,7 @@ from .tensor.logic import bitwise_or  # noqa: F401
 from .tensor.logic import bitwise_xor  # noqa: F401
 from .tensor.logic import not_equal  # noqa: F401
 from .tensor.logic import allclose  # noqa: F401
+from .tensor.logic import isclose  # noqa: F401
 from .tensor.logic import equal_all  # noqa: F401
 from .tensor.logic import is_tensor  # noqa: F401
 from .tensor.manipulation import cast  # noqa: F401
@@ -322,6 +323,7 @@ __all__ = [  # noqa
            'complex128',
            'addmm',
            'allclose',
+           'isclose',
            't',
            'add',
            'subtract',

python/paddle/fluid/tests/unittests/test_isclose_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.
+
+import unittest
+import numpy as np
+from op_test import OpTest
+import paddle
+
+
+class TestIscloseOp(OpTest):
+    def set_args(self):
+        self.input = np.array([10000., 1e-07]).astype("float32")
+        self.other = np.array([10000.1, 1e-08]).astype("float32")
+        self.rtol = np.array([1e-05]).astype("float64")
+        self.atol = np.array([1e-08]).astype("float64")
+        self.equal_nan = False
+
+    def setUp(self):
+        paddle.enable_static()
+        self.set_args()
+        self.op_type = "isclose"
+        self.inputs = {
+            'Input': self.input,
+            'Other': self.other,
+            "Rtol": self.rtol,
+            "Atol": self.atol
+        }
+        self.attrs = {'equal_nan': self.equal_nan}
+        self.outputs = {
+            'Out': np.array([
+                np.isclose(
+                    self.inputs['Input'],
+                    self.inputs['Other'],
+                    rtol=self.rtol,
+                    atol=self.atol,
+                    equal_nan=self.equal_nan)
+            ])
+        }
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestIscloseOpException(TestIscloseOp):
+    def test_check_output(self):
+        def test_rtol_num():
+            self.inputs['Rtol'] = np.array([1e-05, 1e-05]).astype("float64")
+            self.inputs['Atol'] = np.array([1e-08]).astype("float64")
+            self.check_output()
+
+        self.assertRaises(ValueError, test_rtol_num)
+
+        def test_rtol_type():
+            self.inputs['Rtol'] = np.array([5]).astype("int32")
+            self.inputs['Atol'] = np.array([1e-08]).astype("float64")
+            self.check_output()
+
+        self.assertRaises(ValueError, test_rtol_type)
+
+        def test_atol_num():
+            self.inputs['Rtol'] = np.array([1e-05]).astype("float64")
+            self.inputs['Atol'] = np.array([1e-08, 1e-08]).astype("float64")
+            self.check_output()
+
+        self.assertRaises(ValueError, test_atol_num)
+
+        def test_atol_type():
+            self.inputs['Rtol'] = np.array([1e-05]).astype("float64")
+            self.inputs['Atol'] = np.array([8]).astype("int32")
+            self.check_output()
+
+        self.assertRaises(ValueError, test_atol_type)
+
+
+class TestIscloseOpSmallNum(TestIscloseOp):
+    def set_args(self):
+        self.input = np.array([10000., 1e-08]).astype("float32")
+        self.other = np.array([10000.1, 1e-09]).astype("float32")
+        self.rtol = np.array([1e-05]).astype("float64")
+        self.atol = np.array([1e-08]).astype("float64")
+        self.equal_nan = False
+
+
+class TestIscloseOpNanFalse(TestIscloseOp):
+    def set_args(self):
+        self.input = np.array([1.0, float('nan')]).astype("float32")
+        self.other = np.array([1.0, float('nan')]).astype("float32")
+        self.rtol = np.array([1e-05]).astype("float64")
+        self.atol = np.array([1e-08]).astype("float64")
+        self.equal_nan = False
+
+
+class TestIscloseOpNanTrue(TestIscloseOp):
+    def set_args(self):
+        self.input = np.array([1.0, float('nan')]).astype("float32")
+        self.other = np.array([1.0, float('nan')]).astype("float32")
+        self.rtol = np.array([1e-05]).astype("float64")
+        self.atol = np.array([1e-08]).astype("float64")
+        self.equal_nan = True
+
+
+class TestIscloseStatic(unittest.TestCase):
+    def test_api_case(self):
+        paddle.enable_static()
+        x_data = np.random.rand(10, 10)
+        y_data = np.random.rand(10, 10)
+        places = [paddle.fluid.CPUPlace()]
+        if paddle.fluid.core.is_compiled_with_cuda():
+            places.append(paddle.fluid.CUDAPlace(0))
+        for place in places:
+            with paddle.static.program_guard(paddle.static.Program(),
+                                             paddle.static.Program()):
+                x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float64')
+                y = paddle.fluid.data(name='y', shape=[10, 10], dtype='float64')
+                result = paddle.isclose(x, y)
+                exe = paddle.fluid.Executor(place)
+                fetches = exe.run(paddle.fluid.default_main_program(),
+                                  feed={"x": x_data,
+                                        "y": y_data},
+                                  fetch_list=[result])
+                expected_out = np.isclose(x_data, y_data)
+                self.assertTrue((fetches[0] == expected_out).all(), True)
+
+
+class TestIscloseDygraph(unittest.TestCase):
+    def test_api_case(self):
+        places = [paddle.CPUPlace()]
+        if paddle.fluid.core.is_compiled_with_cuda():
+            places.append(paddle.CUDAPlace(0))
+        for place in places:
+            paddle.disable_static()
+            x_data = np.random.rand(10, 10)
+            y_data = np.random.rand(10, 10)
+            x = paddle.to_tensor(x_data, place=place)
+            y = paddle.to_tensor(y_data, place=place)
+            out = paddle.isclose(x, y, rtol=1e-05, atol=1e-08)
+            expected_out = np.isclose(x_data, y_data, rtol=1e-05, atol=1e-08)
+            self.assertTrue((out.numpy() == expected_out).all(), True)
+        paddle.enable_static()
+
+
+class TestIscloseError(unittest.TestCase):
+    def test_input_dtype(self):
+        paddle.enable_static()
+
+        def test_x_dtype():
+            with paddle.static.program_guard(paddle.static.Program(),
+                                             paddle.static.Program()):
+                x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float16')
+                y = paddle.fluid.data(name='y', shape=[10, 10], dtype='float64')
+                result = paddle.isclose(x, y)
+
+        self.assertRaises(TypeError, test_x_dtype)
+
+        def test_y_dtype():
+            with paddle.static.program_guard(paddle.static.Program(),
+                                             paddle.static.Program()):
+                x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float64')
+                y = paddle.fluid.data(name='y', shape=[10, 10], dtype='int32')
+                result = paddle.isclose(x, y)
+
+        self.assertRaises(TypeError, test_y_dtype)
+
+    def test_attr(self):
+        paddle.enable_static()
+        x = paddle.fluid.data(name='x', shape=[10, 10], dtype='float64')
+        y = paddle.fluid.data(name='y', shape=[10, 10], dtype='float64')
+
+        def test_rtol():
+            result = paddle.isclose(x, y, rtol=True)
+
+        self.assertRaises(TypeError, test_rtol)
+
+        def test_atol():
+            result = paddle.isclose(x, y, rtol=True)
+
+        self.assertRaises(TypeError, test_atol)
+
+        def test_equal_nan():
+            result = paddle.isclose(x, y, equal_nan=1)
+
+        self.assertRaises(TypeError, test_equal_nan)
+
+
+class TestIscloseOpFloat32(TestIscloseOp):
+    def set_args(self):
+        self.input = np.array([10.1]).astype("float32")
+        self.other = np.array([10]).astype("float32")
+        self.rtol = np.array([0.01]).astype("float64")
+        self.atol = np.array([0]).astype("float64")
+        self.equal_nan = False
+
+
+class TestIscloseOpFloat64(TestIscloseOp):
+    def set_args(self):
+        self.input = np.array([10.1]).astype("float64")
+        self.other = np.array([10]).astype("float64")
+        self.rtol = np.array([0.01]).astype("float64")
+        self.atol = np.array([0]).astype("float64")
+        self.equal_nan = False
+
+
+class TestIscloseOpLargeDimInput(TestIscloseOp):
+    def set_args(self):
+        self.input = np.array(np.zeros([2048, 1024])).astype("float64")
+        self.other = np.array(np.zeros([2048, 1024])).astype("float64")
+        self.input[-1][-1] = 100
+        self.rtol = np.array([1e-05]).astype("float64")
+        self.atol = np.array([1e-08]).astype("float64")
+        self.equal_nan = False
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/tensor/__init__.py

@@ -72,6 +72,7 @@ from .logic import bitwise_xor  # noqa: F401
 from .logic import bitwise_not  # noqa: F401
 from .logic import not_equal  # noqa: F401
 from .logic import allclose  # noqa: F401
+from .logic import isclose  # noqa: F401
 from .logic import equal_all  # noqa: F401
 from .logic import is_tensor  # noqa: F401
 from .manipulation import cast  # noqa: F401
@@ -331,6 +332,7 @@ tensor_method_func  = [ #noqa
            'logical_xor',
            'not_equal',
            'allclose',
+           'isclose',
            'is_tensor',
            'cast',
            'concat',

python/paddle/tensor/logic.py

@@ -583,3 +583,77 @@ def bitwise_not(x, out=None, name=None):
 
     return _bitwise_op(
         op_name="bitwise_not", x=x, y=None, name=name, out=out, binary_op=False)
+
+
+@templatedoc()
+def isclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
+    """
+    ${comment}
+
+    Args:
+        x(Tensor): ${input_comment}.
+        y(Tensor): ${other_comment}.
+        rtol(rtoltype, optional): The relative tolerance. Default: :math:`1e-5` .
+        atol(atoltype, optional): The absolute tolerance. Default: :math:`1e-8` .
+        equal_nan(equalnantype, optional): ${equal_nan_comment}.
+        name (str, optional): Name for the operation. For more information, please
+            refer to :ref:`api_guide_Name`. Default: None.
+
+    Returns:
+        Tensor: ${out_comment}.
+
+    Raises:
+        TypeError: The data type of ``x`` must be one of float32, float64.
+        TypeError: The data type of ``y`` must be one of float32, float64.
+        TypeError: The type of ``rtol`` must be float.
+        TypeError: The type of ``atol`` must be float.
+        TypeError: The type of ``equal_nan`` must be bool.
+
+    Examples:
+        .. code-block:: python
+
+          import paddle
+
+          x = paddle.to_tensor([10000., 1e-07])
+          y = paddle.to_tensor([10000.1, 1e-08])
+          result1 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08,
+                                  equal_nan=False, name="ignore_nan")
+          np_result1 = result1.numpy()
+          # [True, False]
+          result2 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08,
+                                      equal_nan=True, name="equal_nan")
+          np_result2 = result2.numpy()
+          # [True, False]
+
+          x = paddle.to_tensor([1.0, float('nan')])
+          y = paddle.to_tensor([1.0, float('nan')])
+          result1 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08,
+                                  equal_nan=False, name="ignore_nan")
+          np_result1 = result1.numpy()
+          # [True, False]
+          result2 = paddle.isclose(x, y, rtol=1e-05, atol=1e-08,
+                                      equal_nan=True, name="equal_nan")
+          np_result2 = result2.numpy()
+          # [True, True]
+    """
+
+    if in_dygraph_mode():
+        return _C_ops.isclose(x, y, 'rtol',
+                              str(rtol), 'atol',
+                              str(atol), 'equal_nan', equal_nan)
+
+    check_variable_and_dtype(x, "input", ['float32', 'float64'], 'isclose')
+    check_variable_and_dtype(y, "input", ['float32', 'float64'], 'isclose')
+    check_type(rtol, 'rtol', float, 'isclose')
+    check_type(atol, 'atol', float, 'isclose')
+    check_type(equal_nan, 'equal_nan', bool, 'isclose')
+
+    helper = LayerHelper("isclose", **locals())
+    out = helper.create_variable_for_type_inference(dtype='bool')
+
+    inputs = {'Input': x, 'Other': y}
+    outputs = {'Out': out}
+    attrs = {'rtol': str(rtol), 'atol': str(atol), 'equal_nan': equal_nan}
+    helper.append_op(
+        type='isclose', inputs=inputs, outputs=outputs, attrs=attrs)
+    return out