[Cherry-pick]Fix the accuracy problem of allclose op when using float64 data...

[Cherry-pick]Fix the accuracy problem of allclose op when using float64 data type in static mode.(#29890) (#30313)

* Fix the accuracy problem of allclose op when using float64 data type in static mode.

* Format the code style.

paddle/fluid/operators/allclose_op.cc

@@ -14,7 +14,9 @@
 
 #include "paddle/fluid/operators/allclose_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"
 
@@ -63,9 +65,15 @@ class AllcloseOpMaker : public framework::OpProtoAndCheckerMaker {
              "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.");
-    AddInput("Atol", "The absolute tolerance.");
+    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` .")
@@ -91,8 +99,6 @@ class AllcloseOp : public framework::OperatorWithKernel {
   void InferShape(framework::InferShapeContext* ctx) const override {
     OP_INOUT_CHECK(ctx->HasInput("Input"), "Input", "Input", "Allclose");
     OP_INOUT_CHECK(ctx->HasInput("Other"), "Input", "Other", "Allclose");
-    OP_INOUT_CHECK(ctx->HasInput("Rtol"), "Input", "Rtol", "Allclose");
-    OP_INOUT_CHECK(ctx->HasInput("Atol"), "Input", "Atol", "Allclose");
     OP_INOUT_CHECK(ctx->HasOutput("Out"), "Output", "Out", "Allclose");
 
     auto input_dim = ctx->GetInputDim("Input");
@@ -153,3 +159,16 @@ REGISTER_OPERATOR(
     ops::AllcloseOpVarTypeInference);
 REGISTER_OP_CPU_KERNEL(allclose, ops::AllcloseKernel<CPU, float>,
                        ops::AllcloseKernel<CPU, double>);
+
+REGISTER_OP_VERSION(allclose)
+    .AddCheckpoint(
+        R"ROC(
+      Upgrade allclose add 2 attributes [atol, rtol].
+    )ROC",
+        paddle::framework::compatible::OpVersionDesc()
+            .NewAttr("rtol",
+                     "(string) The relative tolerance. Default: :math:`1e-5` .",
+                     std::string("1e-5"))
+            .NewAttr("atol",
+                     "(string) The absolute tolerance. Default: :math:`1e-8` .",
+                     std::string("1e-8")));

paddle/fluid/operators/allclose_op.h

@@ -14,6 +14,8 @@
 
 #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"
@@ -44,14 +46,38 @@ class AllcloseKernel : public framework::OpKernel<T> {
     // get input/output
     const auto* input = ctx.Input<Tensor>("Input");
     const auto* other = ctx.Input<Tensor>("Other");
-    const auto* rtol = ctx.Input<Tensor>("Rtol");
-    const auto* atol = ctx.Input<Tensor>("Atol");
     auto* out = ctx.Output<Tensor>("Out");
-    auto& dev_ctx = ctx.template device_context<DeviceContext>();
 
+    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;
-    double rtol_v = get_tensor_value(dev_ctx, *rtol);
-    double atol_v = get_tensor_value(dev_ctx, *atol);
+    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);
+    }
+
     AllcloseFunctor<DeviceContext, T>()(dev_ctx, *input, *other, rtol_v, atol_v,
                                         equal_nan, out);
   }

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

@@ -19,57 +19,81 @@ import numpy as np
 
 
 class TestAllcloseLayer(unittest.TestCase):
-    def allclose_check(self, use_cuda):
-        a = fluid.data(name="a", shape=[2], dtype='float32')
-        b = fluid.data(name="b", shape=[2], dtype='float32')
+    def allclose_check(self, use_cuda, dtype='float32'):
+        a = fluid.data(name="a", shape=[2], dtype=dtype)
+        b = fluid.data(name="b", shape=[2], dtype=dtype)
 
         result = paddle.allclose(
             a, b, rtol=1e-05, atol=1e-08, equal_nan=False, name="ignore_nan")
         result_nan = paddle.allclose(
             a, b, rtol=1e-05, atol=1e-08, equal_nan=True, name="equal_nan")
+        result_corner = paddle.allclose(
+            a, b, rtol=0.01, atol=0.0, name="corner_case")
 
         place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace()
         exe = fluid.Executor(place)
         exe.run(fluid.default_startup_program())
 
-        x = np.array([10000., 1e-07]).astype("float32")
-        y = np.array([10000.1, 1e-08]).astype("float32")
+        x = np.array([10000., 1e-07]).astype(dtype)
+        y = np.array([10000.1, 1e-08]).astype(dtype)
         result_v, result_nan_v = exe.run(feed={'a': x,
                                                'b': y},
                                          fetch_list=[result, result_nan])
         self.assertEqual(result_v[0], False)
         self.assertEqual(result_nan_v[0], False)
 
-        x = np.array([10000., 1e-08]).astype("float32")
-        y = np.array([10000.1, 1e-09]).astype("float32")
+        x = np.array([10000., 1e-08]).astype(dtype)
+        y = np.array([10000.1, 1e-09]).astype(dtype)
         result_v, result_nan_v = exe.run(feed={'a': x,
                                                'b': y},
                                          fetch_list=[result, result_nan])
         self.assertEqual(result_v[0], True)
         self.assertEqual(result_nan_v[0], True)
 
-        x = np.array([1.0, float('nan')]).astype("float32")
-        y = np.array([1.0, float('nan')]).astype("float32")
+        x = np.array([1.0, float('nan')]).astype(dtype)
+        y = np.array([1.0, float('nan')]).astype(dtype)
         result_v, result_nan_v = exe.run(feed={'a': x,
                                                'b': y},
                                          fetch_list=[result, result_nan])
         self.assertEqual(result_v[0], False)
         self.assertEqual(result_nan_v[0], True)
 
-    def test_allclose_cpu(self):
+        # for corner case
+        x = np.array([10.1, 10.1]).astype(dtype)
+        y = np.array([10, 10]).astype(dtype)
+        result_c, = exe.run(feed={'a': x, 'b': y}, fetch_list=[result_corner])
+        corner_res = (dtype == 'float64')
+        self.assertEqual(result_c[0], corner_res)
+
+    def test_allclose_cpu_fp32(self):
+        main = fluid.Program()
+        startup = fluid.Program()
+        with fluid.unique_name.guard():
+            with fluid.program_guard(main, startup):
+                self.allclose_check(use_cuda=False, dtype='float32')
+
+    def test_allclose_cpu_fp64(self):
+        main = fluid.Program()
+        startup = fluid.Program()
+        with fluid.unique_name.guard():
+            with fluid.program_guard(main, startup):
+                self.allclose_check(use_cuda=False, dtype='float64')
+
+    def test_allclose_gpu_fp32(self):
+        if fluid.core.is_compiled_with_cuda():
             main = fluid.Program()
             startup = fluid.Program()
             with fluid.unique_name.guard():
                 with fluid.program_guard(main, startup):
-                self.allclose_check(use_cuda=False)
+                    self.allclose_check(use_cuda=True, dtype='float32')
 
-    def test_allclose_gpu(self):
+    def test_allclose_gpu_fp64(self):
         if fluid.core.is_compiled_with_cuda():
             main = fluid.Program()
             startup = fluid.Program()
             with fluid.unique_name.guard():
                 with fluid.program_guard(main, startup):
-                    self.allclose_check(use_cuda=True)
+                    self.allclose_check(use_cuda=True, dtype='float64')
 
     def test_dygraph_mode(self):
         x_1 = np.array([10000., 1e-07]).astype("float32")
@@ -78,10 +102,14 @@ class TestAllcloseLayer(unittest.TestCase):
         y_2 = np.array([10000.1, 1e-09]).astype("float32")
         x_3 = np.array([1.0, float('nan')]).astype("float32")
         y_3 = np.array([1.0, float('nan')]).astype("float32")
+        x_4 = np.array([10.1]).astype("float32")
+        y_4 = np.array([10]).astype("float32")
+        x_5 = np.array([10.1]).astype("float64")
+        y_5 = np.array([10]).astype("float64")
 
         with fluid.dygraph.guard():
-            x_v_1 = fluid.dygraph.to_variable(x_1)
-            y_v_1 = fluid.dygraph.to_variable(y_1)
+            x_v_1 = paddle.to_tensor(x_1)
+            y_v_1 = paddle.to_tensor(y_1)
             ret_1 = paddle.allclose(
                 x_v_1,
                 y_v_1,
@@ -98,8 +126,8 @@ class TestAllcloseLayer(unittest.TestCase):
                 equal_nan=True,
                 name='test_2')
             self.assertEqual(ret_1.numpy()[0], False)
-            x_v_2 = fluid.dygraph.to_variable(x_2)
-            y_v_2 = fluid.dygraph.to_variable(y_2)
+            x_v_2 = paddle.to_tensor(x_2)
+            y_v_2 = paddle.to_tensor(y_2)
             ret_2 = paddle.allclose(
                 x_v_2,
                 y_v_2,
@@ -116,8 +144,8 @@ class TestAllcloseLayer(unittest.TestCase):
                 equal_nan=True,
                 name='test_4')
             self.assertEqual(ret_2.numpy()[0], True)
-            x_v_3 = fluid.dygraph.to_variable(x_3)
-            y_v_3 = fluid.dygraph.to_variable(y_3)
+            x_v_3 = paddle.to_tensor(x_3)
+            y_v_3 = paddle.to_tensor(y_3)
             ret_3 = paddle.allclose(
                 x_v_3,
                 y_v_3,
@@ -134,6 +162,17 @@ class TestAllcloseLayer(unittest.TestCase):
                 equal_nan=True,
                 name='test_6')
             self.assertEqual(ret_3.numpy()[0], True)
+            # for corner case
+            x_v_4 = paddle.to_tensor(x_4)
+            y_v_4 = paddle.to_tensor(y_4)
+            ret_4 = paddle.allclose(
+                x_v_4, y_v_4, rtol=0.01, atol=0.0, name='test_7')
+            self.assertEqual(ret_4.numpy()[0], False)
+            x_v_5 = paddle.to_tensor(x_5)
+            y_v_5 = paddle.to_tensor(y_5)
+            ret_5 = paddle.allclose(
+                x_v_5, y_v_5, rtol=0.01, atol=0.0, name='test_8')
+            self.assertEqual(ret_5.numpy()[0], True)
 
 
 if __name__ == "__main__":

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

@@ -51,6 +51,37 @@ class TestAllcloseOp(OpTest):
         self.check_output()
 
 
+class TestAllcloseOpException(TestAllcloseOp):
+    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 TestAllcloseOpSmallNum(TestAllcloseOp):
     def set_args(self):
         self.input = np.array([10000., 1e-08]).astype("float32")

python/paddle/tensor/logic.py

@@ -12,7 +12,6 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from . import to_tensor
 from ..fluid.layer_helper import LayerHelper
 from ..fluid.data_feeder import check_type, check_variable_and_dtype
 from ..fluid.layers.layer_function_generator import templatedoc
@@ -137,10 +136,9 @@ def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
     """
 
     if in_dygraph_mode():
-        rtol_tensor = to_tensor(rtol, dtype='float64')
-        atol_tensor = to_tensor(atol, dtype='float64')
-        return core.ops.allclose(x, y, rtol_tensor, atol_tensor, 'equal_nan',
-                                 equal_nan)
+        return core.ops.allclose(x, y, 'rtol',
+                                 str(rtol), 'atol',
+                                 str(atol), 'equal_nan', equal_nan)
 
     check_variable_and_dtype(x, "input", ['float32', 'float64'], 'allclose')
     check_variable_and_dtype(y, "input", ['float32', 'float64'], 'allclose')
@@ -149,26 +147,11 @@ def allclose(x, y, rtol=1e-05, atol=1e-08, equal_nan=False, name=None):
     check_type(equal_nan, 'equal_nan', bool, 'allclose')
 
     helper = LayerHelper("allclose", **locals())
-    rtol_var = helper.create_global_variable(
-        name=fluid.unique_name.generate('rtol'),
-        persistable=True,
-        dtype='float64',
-        shape=[1])
-    helper.set_variable_initializer(
-        rtol_var, initializer=fluid.initializer.ConstantInitializer(rtol))
-    atol_var = helper.create_variable(
-        name=fluid.unique_name.generate('atol'),
-        persistable=True,
-        dtype='float64',
-        shape=[1])
-    helper.set_variable_initializer(
-        atol_var, initializer=fluid.initializer.ConstantInitializer(atol))
-
     out = helper.create_variable_for_type_inference(dtype='bool')
 
-    inputs = {'Input': x, 'Other': y, 'Rtol': rtol_var, 'Atol': atol_var}
+    inputs = {'Input': x, 'Other': y}
     outputs = {'Out': out}
-    attrs = {'equal_nan': equal_nan}
+    attrs = {'rtol': str(rtol), 'atol': str(atol), 'equal_nan': equal_nan}
     helper.append_op(
         type='allclose', inputs=inputs, outputs=outputs, attrs=attrs)