From 99c88f3a04986ba89e438315d33d0e37fad5089f Mon Sep 17 00:00:00 2001
From: Chen Weihang <chenweihang@baidu.com>
Date: Wed, 28 Oct 2020 12:25:43 +0000
Subject: [PATCH 1/6] check and fix tensor and scalar type promotion

---
 python/paddle/fluid/dygraph/math_op_patch.py  |  40 +-
 python/paddle/fluid/layers/math_op_patch.py   |  37 +-
 ...st_tensor_scalar_type_promotion_dynamic.py | 318 +++++++++++++++
 ...est_tensor_scalar_type_promotion_static.py | 369 ++++++++++++++++++
 4 files changed, 737 insertions(+), 27 deletions(-)
 create mode 100644 python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py
 create mode 100644 python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_static.py

diff --git a/python/paddle/fluid/dygraph/math_op_patch.py b/python/paddle/fluid/dygraph/math_op_patch.py
index 68206f62860852..e4dba3b9eae998 100644
--- a/python/paddle/fluid/dygraph/math_op_patch.py
+++ b/python/paddle/fluid/dygraph/math_op_patch.py
@@ -149,21 +149,31 @@ def _binary_creator_(method_name,
                          reverse=False,
                          scalar_method=None):
         def __impl__(self, other_var):
-            # FIXME(zjl): elementwise_div between integers cannot be converted to scale,
-            # which may lose accuracy. This is a hot fix for release 1.6.
-            if scalar_method is not None and not (
-                    op_type == 'elementwise_div' and
-                    self.dtype in _supported_int_dtype_):
-                if isinstance(other_var, float):
-                    if self.dtype in _supported_int_dtype_:
-                        assert other_var == int(other_var), \
-                            "float value {} cannot convert to integer".format(other_var)
-                    return scalar_method(self, other_var)
-                elif isinstance(other_var, int):
-                    return scalar_method(self, float(other_var))
-
+            # 1. scalar exists cases
+            # we need combine the tensor.dtype and scalar.dtype, cast correct object
+            if isinstance(other_var, float):
+                # in all cases(+, -, *, /, **, //, %), we need cast tensor.dtype to float
+                if self.dtype in _supported_int_dtype_:
+                    self = astype(self, 'float32')
+            elif isinstance(other_var, int):
+                # in all cases(+, -, *, /, **, //, %), we can cast it to float
+                # because the output tensor.dtype depend on the type of input tensor
+                other_var = float(other_var)
+                # division is a special case
+                if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
+                    self = astype(self, 'float32')
+            else:
+                raise TypeError(
+                    "Only supports scalar operations of `int` and `float` now.")
+
+            # 2. scalar method selected
+            # here use `scale` replace `elementwise` to get better performance
+            # but only +, -, *, / can use this method
+            if scalar_method is not None:
+                return scalar_method(self, other_var)
+
+            # 3. create varbase for scalar
             lhs_dtype = self.dtype
-
             if not isinstance(other_var, core.VarBase):
                 if reverse:
                     other_var = create_tensor(
@@ -172,6 +182,7 @@ def __impl__(self, other_var):
                     # add fill_op 
                     other_var = create_scalar(value=other_var, dtype=lhs_dtype)
 
+            # 4. unify right var type to left var
             rhs_dtype = other_var.dtype
             if lhs_dtype != rhs_dtype:
                 other_var = astype(other_var, lhs_dtype)
@@ -180,6 +191,7 @@ def __impl__(self, other_var):
                 self = other_var
                 other_var = tmp
 
+            # 5. calculation
             axis = -1
             math_op = getattr(core.ops, op_type)
             return math_op(self, other_var, 'axis', axis)
diff --git a/python/paddle/fluid/layers/math_op_patch.py b/python/paddle/fluid/layers/math_op_patch.py
index 92b58a7e2ee4c7..7fde3632753460 100644
--- a/python/paddle/fluid/layers/math_op_patch.py
+++ b/python/paddle/fluid/layers/math_op_patch.py
@@ -215,21 +215,31 @@ def _binary_creator_(method_name,
                          reverse=False,
                          scalar_method=None):
         def __impl__(self, other_var):
-            # FIXME(zjl): elementwise_div between integers cannot be converted to scale,
-            # which may lose accuracy. This is a hot fix for release 1.6.
-            if scalar_method is not None and not (
-                    op_type == 'elementwise_div' and
-                    self.dtype in _supported_int_dtype_):
-                if isinstance(other_var, float):
-                    if self.dtype in _supported_int_dtype_:
-                        assert other_var == int(other_var), \
-                            "float value {} cannot convert to integer".format(other_var)
-                    return scalar_method(self, other_var)
-                elif isinstance(other_var, int):
-                    return scalar_method(self, float(other_var))
+            # 1. scalar exists cases
+            # we need combine the tensor.dtype and scalar.dtype, cast correct object
+            if isinstance(other_var, float):
+                # in all cases(+, -, *, /, **, //, %), we need cast tensor.dtype to float
+                if self.dtype in _supported_int_dtype_:
+                    self = astype(self, 'float32')
+            elif isinstance(other_var, int):
+                # in all cases(+, -, *, /, **, //, %), we can cast it to float
+                # because the output tensor.dtype depend on the type of input tensor
+                other_var = float(other_var)
+                # division is a special case
+                if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
+                    self = astype(self, 'float32')
+            else:
+                raise TypeError(
+                    "Only supports scalar operations of `int` and `float` now.")
 
-            lhs_dtype = safe_get_dtype(self)
+            # 2. scalar method selected
+            # here use `scale` replace `elementwise` to get better performance
+            # but only +, -, *, / can use this method
+            if scalar_method is not None:
+                return scalar_method(self, other_var)
 
+            # 3. create variable for scalar
+            lhs_dtype = safe_get_dtype(self)
             if not isinstance(other_var, Variable):
                 if reverse:
                     has_batch_size = False
@@ -251,6 +261,7 @@ def __impl__(self, other_var):
                     other_var = create_scalar(
                         current_block(self), value=other_var, dtype=lhs_dtype)
 
+            # 4. unify right var type to left var
             rhs_dtype = safe_get_dtype(other_var)
             if lhs_dtype != rhs_dtype:
                 other_var = astype(other_var, lhs_dtype)
diff --git a/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py b/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py
new file mode 100644
index 00000000000000..5f2dfbdd99e161
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_dynamic.py
@@ -0,0 +1,318 @@
+#   Copyright (c) 2020 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, division
+
+import unittest
+import numpy as np
+
+import paddle
+
+# Support types are ref from `paddle.tensor.math`
+# - Related paddle dtypes:
+#  - int type: int64, (no test here: uint8, int8, int16, int32)
+#  - float type: float32, (no test here: float64)
+# - Python scalar dtypes: 
+#  - int(64)
+#  - float(64)
+
+
+class TestTensorScalarTypePromotionDynamic(unittest.TestCase):
+    def check_operation(self, a, b, c, op):
+        if op == '+':
+            c_rlt = a + b
+        elif op == '-':
+            c_rlt = a - b
+        elif op == '*':
+            c_rlt = a * b
+        elif op == '/':
+            c_rlt = a / b
+        elif op == '**':
+            c_rlt = a**b
+        elif op == '//':
+            c_rlt = a // b
+        elif op == '%':
+            c_rlt = a % b
+        else:
+            raise ValueError("Unsupported operation.")
+
+        self.assertEqual(c_rlt.dtype, c.dtype)
+        self.assertTrue(np.array_equal(c_rlt.numpy(), c.numpy()))
+
+    def test_tensor_add_scalar(self):
+        # tensor(int64) + scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1
+        c = paddle.full([2, 2, 2], 2, dtype="int64")
+        self.check_operation(a, b, c, '+')
+
+        # tensor(float32) + scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 1
+        c = paddle.full([2, 2, 2], 2, dtype="float32")
+        self.check_operation(a, b, c, '+')
+
+        # tensor(int64) + scalar(float, .0)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1.0
+        c = paddle.full([2, 2, 2], 2, dtype="float32")
+        self.check_operation(a, b, c, '+')
+
+        # tensor(int64) + scalar(float, .5)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1.5
+        c = paddle.full([2, 2, 2], 2.5, dtype="float32")
+        self.check_operation(a, b, c, '+')
+
+        # tensor(float32) + scalar(float)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 1.5
+        c = paddle.full([2, 2, 2], 2.5, dtype="float32")
+        self.check_operation(a, b, c, '+')
+
+    def test_tensor_sub_scalar(self):
+        # tensor(int64) - scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1
+        c = paddle.zeros([2, 2, 2], dtype="int64")
+        self.check_operation(a, b, c, '-')
+
+        # tensor(float32) - scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 1
+        c = paddle.zeros([2, 2, 2], dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+        # tensor(int64) - scalar(float, .0)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1.0
+        c = paddle.zeros([2, 2, 2], dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+        # tensor(int64) - scalar(float, .5)
+        a = paddle.full([2, 2, 2], 2, dtype='int64')
+        b = 1.5
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+        # tensor(float32) - scalar(float)
+        a = paddle.full([2, 2, 2], 2, dtype='float32')
+        b = 1.5
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+    def test_scalar_sub_tensor(self):
+        # scalar(int) - tensor(int64)
+        a = 1
+        b = paddle.ones([2, 2, 2], dtype='int64')
+        c = paddle.zeros([2, 2, 2], dtype="int64")
+        self.check_operation(a, b, c, '-')
+
+        # scalar(int) - tensor(float32)
+        a = 1
+        b = paddle.ones([2, 2, 2], dtype='float32')
+        c = paddle.zeros([2, 2, 2], dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+        # scalar(float, .0) - tensor(int64)
+        a = 1.0
+        b = paddle.ones([2, 2, 2], dtype='int64')
+        c = paddle.zeros([2, 2, 2], dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+        # scalar(float, .5) - tensor(int64)
+        a = 1.5
+        b = paddle.full([2, 2, 2], 2, dtype='int64')
+        c = paddle.full([2, 2, 2], -0.5, dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+        # scalar(float) - tensor(float32)
+        a = 1.5
+        b = paddle.full([2, 2, 2], 2, dtype='float32')
+        c = paddle.full([2, 2, 2], -0.5, dtype="float32")
+        self.check_operation(a, b, c, '-')
+
+    def test_tensor_mul_tensor(self):
+        # tensor(int64) * scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1
+        c = paddle.ones([2, 2, 2], dtype="int64")
+        self.check_operation(a, b, c, '*')
+
+        # tensor(float32) * scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 1
+        c = paddle.ones([2, 2, 2], dtype="float32")
+        self.check_operation(a, b, c, '*')
+
+        # tensor(int64) * scalar(float, .0)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1.0
+        c = paddle.ones([2, 2, 2], dtype="float32")
+        self.check_operation(a, b, c, '*')
+
+        # tensor(int64) * scalar(float, .5)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 1.5
+        c = paddle.full([2, 2, 2], 1.5, dtype="float32")
+        self.check_operation(a, b, c, '*')
+
+        # tensor(float32) * scalar(float)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 1.5
+        c = paddle.full([2, 2, 2], 1.5, dtype="float32")
+        self.check_operation(a, b, c, '*')
+
+    def test_tensor_div_scalar(self):
+        # tensor(int64) / scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 2
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # tensor(float32) / scalar(int)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 2
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # tensor(int64) / scalar(float, .0)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 2.0
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # tensor(int64) / scalar(float, .5)
+        a = paddle.ones([2, 2, 2], dtype='int64')
+        b = 0.5
+        c = paddle.full([2, 2, 2], 2, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # tensor(float32) / scalar(float)
+        a = paddle.ones([2, 2, 2], dtype='float32')
+        b = 0.5
+        c = paddle.full([2, 2, 2], 2, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+    def test_scalar_div_tensor(self):
+        # scalar(int) / tensor(int64)
+        a = 1
+        b = paddle.full([2, 2, 2], 2, dtype='int64')
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # scalar(int) / tensor(float32)
+        a = 1
+        b = paddle.full([2, 2, 2], 0.5, dtype='float32')
+        c = paddle.full([2, 2, 2], 2, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # scalar(float) / tensor(int64)
+        a = 1.0
+        b = paddle.full([2, 2, 2], 2, dtype='int64')
+        c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+        # scalar(float) / tensor(float32)
+        a = 1.0
+        b = paddle.full([2, 2, 2], 0.5, dtype='float32')
+        c = paddle.full([2, 2, 2], 2, dtype="float32")
+        self.check_operation(a, b, c, '/')
+
+    def test_tensor_pow_scalar(self):
+        # tensor(int64) ** scalar(int)
+        a = paddle.full([2, 2, 2], 2, dtype='int64')
+        b = 3
+        c = paddle.full([2, 2, 2], 8, dtype="int64")
+        self.check_operation(a, b, c, '**')
+
+        # tensor(int64) ** scalar(float)
+        a = paddle.full([2, 2, 2], 2, dtype='int64')
+        b = 3.0
+        c = paddle.full([2, 2, 2], 8, dtype="float32")
+        self.check_operation(a, b, c, '**')
+
+        # tensor(float32) ** scalar(int)
+        a = paddle.full([2, 2, 2], 2, dtype='float32')
+        b = 3
+        c = paddle.full([2, 2, 2], 8, dtype="float32")
+        self.check_operation(a, b, c, '**')
+
+        # tensor(float32) ** scalar(float)
+        a = paddle.full([2, 2, 2], 2, dtype='float32')
+        b = 3.0
+        c = paddle.full([2, 2, 2], 8, dtype="float32")
+        self.check_operation(a, b, c, '**')
+
+    def test_scalar_pow_tensor(self):
+        # scalar(int) ** tensor(int64)
+        a = 3
+        b = paddle.full([2, 2, 2], 2, dtype='int64')
+        c = paddle.full([2, 2, 2], 9, dtype="int64")
+        self.check_operation(a, b, c, '**')
+
+        # scalar(float) ** tensor(int64)
+        a = 3.0
+        b = paddle.full([2, 2, 2], 2, dtype='int64')
+        c = paddle.full([2, 2, 2], 9, dtype="float32")
+        self.check_operation(a, b, c, '**')
+
+        # scalar(int) ** tensor(float32)
+        a = 3
+        b = paddle.full([2, 2, 2], 2, dtype='float32')
+        c = paddle.full([2, 2, 2], 9, dtype="float32")
+        self.check_operation(a, b, c, '**')
+
+        # tensor(float32) ** scalar(float)
+        a = 3.0
+        b = paddle.full([2, 2, 2], 2, dtype='float32')
+        c = paddle.full([2, 2, 2], 9, dtype="float32")
+        self.check_operation(a, b, c, '**')
+
+    ## TODO: floordiv op kernel doesn't support float
+    def test_tensor_floordiv_scalar(self):
+        # tensor(int64) // scalar(int)
+        a = paddle.full([2, 2, 2], 3, dtype='int64')
+        b = 2
+        c = paddle.full([2, 2, 2], 1, dtype="int64")
+        self.check_operation(a, b, c, '//')
+
+    def test_tensor_mod_scalar(self):
+        # tensor(int64) % scalar(int)
+        a = paddle.full([2, 2, 2], 3, dtype='int64')
+        b = 2
+        c = paddle.full([2, 2, 2], 1, dtype="int64")
+        self.check_operation(a, b, c, '%')
+
+        # tensor(int64) % scalar(float)
+        a = paddle.full([2, 2, 2], 3, dtype='int64')
+        b = 2.0
+        c = paddle.full([2, 2, 2], 1, dtype="float32")
+        self.check_operation(a, b, c, '%')
+
+        # tensor(float32) % scalar(int)
+        a = paddle.full([2, 2, 2], 3, dtype='float32')
+        b = 2
+        c = paddle.full([2, 2, 2], 1, dtype="float32")
+        self.check_operation(a, b, c, '%')
+
+        # tensor(float32) % scalar(float)
+        a = paddle.full([2, 2, 2], 3, dtype='float32')
+        b = 2.0
+        c = paddle.full([2, 2, 2], 1, dtype="float32")
+        self.check_operation(a, b, c, '%')
+
+
+if __name__ == '__main__':
+    unittest.main()
diff --git a/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_static.py b/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_static.py
new file mode 100644
index 00000000000000..d697666e12ddd1
--- /dev/null
+++ b/python/paddle/fluid/tests/unittests/test_tensor_scalar_type_promotion_static.py
@@ -0,0 +1,369 @@
+#   Copyright (c) 2020 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, division
+
+import unittest
+import numpy as np
+
+import paddle
+from paddle.static import program_guard
+from paddle.static import Program
+
+# Support types are ref from `paddle.tensor.math`
+# - Related paddle dtypes:
+#  - int type: int64, (no test here: uint8, int8, int16, int32)
+#  - float type: float32, (no test here: float64)
+# - Python scalar dtypes: 
+#  - int(64)
+#  - float(64)
+
+
+class TestTensorScalarTypePromotionStatic(unittest.TestCase):
+    def setUp(self):
+        paddle.enable_static()
+
+    def check_operation(self, a, b, c, op):
+        exe = paddle.static.Executor()
+
+        if op == '+':
+            c_rlt = a + b
+        elif op == '-':
+            c_rlt = a - b
+        elif op == '*':
+            c_rlt = a * b
+        elif op == '/':
+            c_rlt = a / b
+        elif op == '**':
+            c_rlt = a**b
+        elif op == '//':
+            c_rlt = a // b
+        elif op == '%':
+            c_rlt = a % b
+        else:
+            raise ValueError("Unsupported operation.")
+
+        rlt = exe.run(fetch_list=[c_rlt.name, c.name])
+
+        self.assertEqual(rlt[0].dtype, rlt[1].dtype)
+        self.assertTrue(np.array_equal(rlt[0], rlt[1]))
+
+    def test_tensor_add_scalar(self):
+        # tensor(int64) + scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1
+            c = paddle.full([2, 2, 2], 2, dtype="int64")
+            self.check_operation(a, b, c, '+')
+
+        # tensor(float32) + scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 1
+            c = paddle.full([2, 2, 2], 2, dtype="float32")
+            self.check_operation(a, b, c, '+')
+
+        # tensor(int64) + scalar(float, .0)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1.0
+            c = paddle.full([2, 2, 2], 2, dtype="float32")
+            self.check_operation(a, b, c, '+')
+
+        # tensor(int64) + scalar(float, .5)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1.5
+            c = paddle.full([2, 2, 2], 2.5, dtype="float32")
+            self.check_operation(a, b, c, '+')
+
+        # tensor(float32) + scalar(float)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 1.5
+            c = paddle.full([2, 2, 2], 2.5, dtype="float32")
+            self.check_operation(a, b, c, '+')
+
+    def test_tensor_sub_scalar(self):
+        # tensor(int64) - scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1
+            c = paddle.zeros([2, 2, 2], dtype="int64")
+            self.check_operation(a, b, c, '-')
+
+        # tensor(float32) - scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 1
+            c = paddle.zeros([2, 2, 2], dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+        # tensor(int64) - scalar(float, .0)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1.0
+            c = paddle.zeros([2, 2, 2], dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+        # tensor(int64) - scalar(float, .5)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 2, dtype='int64')
+            b = 1.5
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+        # tensor(float32) - scalar(float)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 2, dtype='float32')
+            b = 1.5
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+    def test_scalar_sub_tensor(self):
+        # scalar(int) - tensor(int64)
+        with program_guard(Program()):
+            a = 1
+            b = paddle.ones([2, 2, 2], dtype='int64')
+            c = paddle.zeros([2, 2, 2], dtype="int64")
+            self.check_operation(a, b, c, '-')
+
+        # scalar(int) - tensor(float32)
+        with program_guard(Program()):
+            a = 1
+            b = paddle.ones([2, 2, 2], dtype='float32')
+            c = paddle.zeros([2, 2, 2], dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+        # scalar(float, .0) - tensor(int64)
+        with program_guard(Program()):
+            a = 1.0
+            b = paddle.ones([2, 2, 2], dtype='int64')
+            c = paddle.zeros([2, 2, 2], dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+        # scalar(float, .5) - tensor(int64)
+        with program_guard(Program()):
+            a = 1.5
+            b = paddle.full([2, 2, 2], 2, dtype='int64')
+            c = paddle.full([2, 2, 2], -0.5, dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+        # scalar(float) - tensor(float32)
+        with program_guard(Program()):
+            a = 1.5
+            b = paddle.full([2, 2, 2], 2, dtype='float32')
+            c = paddle.full([2, 2, 2], -0.5, dtype="float32")
+            self.check_operation(a, b, c, '-')
+
+    def test_tensor_mul_tensor(self):
+        # tensor(int64) * scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1
+            c = paddle.ones([2, 2, 2], dtype="int64")
+            self.check_operation(a, b, c, '*')
+
+        # tensor(float32) * scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 1
+            c = paddle.ones([2, 2, 2], dtype="float32")
+            self.check_operation(a, b, c, '*')
+
+        # tensor(int64) * scalar(float, .0)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1.0
+            c = paddle.ones([2, 2, 2], dtype="float32")
+            self.check_operation(a, b, c, '*')
+
+        # tensor(int64) * scalar(float, .5)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 1.5
+            c = paddle.full([2, 2, 2], 1.5, dtype="float32")
+            self.check_operation(a, b, c, '*')
+
+        # tensor(float32) * scalar(float)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 1.5
+            c = paddle.full([2, 2, 2], 1.5, dtype="float32")
+            self.check_operation(a, b, c, '*')
+
+    def test_tensor_div_scalar(self):
+        # tensor(int64) / scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 2
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # tensor(float32) / scalar(int)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 2
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # tensor(int64) / scalar(float, .0)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 2.0
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # tensor(int64) / scalar(float, .5)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='int64')
+            b = 0.5
+            c = paddle.full([2, 2, 2], 2, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # tensor(float32) / scalar(float)
+        with program_guard(Program()):
+            a = paddle.ones([2, 2, 2], dtype='float32')
+            b = 0.5
+            c = paddle.full([2, 2, 2], 2, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+    def test_scalar_div_tensor(self):
+        # scalar(int) / tensor(int64)
+        with program_guard(Program()):
+            a = 1
+            b = paddle.full([2, 2, 2], 2, dtype='int64')
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # scalar(int) / tensor(float32)
+        with program_guard(Program()):
+            a = 1
+            b = paddle.full([2, 2, 2], 0.5, dtype='float32')
+            c = paddle.full([2, 2, 2], 2, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # scalar(float) / tensor(int64)
+        with program_guard(Program()):
+            a = 1.0
+            b = paddle.full([2, 2, 2], 2, dtype='int64')
+            c = paddle.full([2, 2, 2], 0.5, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+        # scalar(float) / tensor(float32)
+        with program_guard(Program()):
+            a = 1.0
+            b = paddle.full([2, 2, 2], 0.5, dtype='float32')
+            c = paddle.full([2, 2, 2], 2, dtype="float32")
+            self.check_operation(a, b, c, '/')
+
+    def test_tensor_pow_scalar(self):
+        # tensor(int64) ** scalar(int)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 2, dtype='int64')
+            b = 3
+            c = paddle.full([2, 2, 2], 8, dtype="int64")
+            self.check_operation(a, b, c, '**')
+
+        # tensor(int64) ** scalar(float)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 2, dtype='int64')
+            b = 3.0
+            c = paddle.full([2, 2, 2], 8, dtype="float32")
+            self.check_operation(a, b, c, '**')
+
+        # tensor(float32) ** scalar(int)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 2, dtype='float32')
+            b = 3
+            c = paddle.full([2, 2, 2], 8, dtype="float32")
+            self.check_operation(a, b, c, '**')
+
+        # tensor(float32) ** scalar(float)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 2, dtype='float32')
+            b = 3.0
+            c = paddle.full([2, 2, 2], 8, dtype="float32")
+            self.check_operation(a, b, c, '**')
+
+    def test_scalar_pow_tensor(self):
+        # scalar(int) ** tensor(int64)
+        with program_guard(Program()):
+            a = 3
+            b = paddle.full([2, 2, 2], 2, dtype='int64')
+            c = paddle.full([2, 2, 2], 9, dtype="int64")
+            self.check_operation(a, b, c, '**')
+
+        # scalar(float) ** tensor(int64)
+        with program_guard(Program()):
+            a = 3.0
+            b = paddle.full([2, 2, 2], 2, dtype='int64')
+            c = paddle.full([2, 2, 2], 9, dtype="float32")
+            self.check_operation(a, b, c, '**')
+
+        # scalar(int) ** tensor(float32)
+        with program_guard(Program()):
+            a = 3
+            b = paddle.full([2, 2, 2], 2, dtype='float32')
+            c = paddle.full([2, 2, 2], 9, dtype="float32")
+            self.check_operation(a, b, c, '**')
+
+        # tensor(float32) ** scalar(float)
+        with program_guard(Program()):
+            a = 3.0
+            b = paddle.full([2, 2, 2], 2, dtype='float32')
+            c = paddle.full([2, 2, 2], 9, dtype="float32")
+            self.check_operation(a, b, c, '**')
+
+    # ## TODO: floordiv op kernel doesn't support float
+    def test_tensor_floordiv_scalar(self):
+        # tensor(int64) // scalar(int)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 3, dtype='int64')
+            b = 2
+            c = paddle.full([2, 2, 2], 1, dtype="int64")
+            self.check_operation(a, b, c, '//')
+
+    def test_tensor_mod_scalar(self):
+        # tensor(int64) % scalar(int)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 3, dtype='int64')
+            b = 2
+            c = paddle.full([2, 2, 2], 1, dtype="int64")
+            self.check_operation(a, b, c, '%')
+
+        # tensor(int64) % scalar(float)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 3, dtype='int64')
+            b = 2.0
+            c = paddle.full([2, 2, 2], 1, dtype="float32")
+            self.check_operation(a, b, c, '%')
+
+        # tensor(float32) % scalar(int)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 3, dtype='float32')
+            b = 2
+            c = paddle.full([2, 2, 2], 1, dtype="float32")
+            self.check_operation(a, b, c, '%')
+
+        # tensor(float32) % scalar(float)
+        with program_guard(Program()):
+            a = paddle.full([2, 2, 2], 3, dtype='float32')
+            b = 2.0
+            c = paddle.full([2, 2, 2], 1, dtype="float32")
+            self.check_operation(a, b, c, '%')
+
+
+if __name__ == '__main__':
+    unittest.main()

From f1538926dca479fe1962f4baf27469a5cf34b848 Mon Sep 17 00:00:00 2001
From: Chen Weihang <chenweihang@baidu.com>
Date: Wed, 28 Oct 2020 14:30:22 +0000
Subject: [PATCH 2/6] fix else branch error

---
 python/paddle/fluid/dygraph/math_op_patch.py    |   4 ++--
 python/paddle/fluid/layers/math_op_patch.py     |   4 ++--
 .../static_mode_white_list.cpython-35.pyc       | Bin 0 -> 19105 bytes
 3 files changed, 4 insertions(+), 4 deletions(-)
 create mode 100644 tools/__pycache__/static_mode_white_list.cpython-35.pyc

diff --git a/python/paddle/fluid/dygraph/math_op_patch.py b/python/paddle/fluid/dygraph/math_op_patch.py
index e4dba3b9eae998..d5d8e763c6978e 100644
--- a/python/paddle/fluid/dygraph/math_op_patch.py
+++ b/python/paddle/fluid/dygraph/math_op_patch.py
@@ -163,8 +163,8 @@ def __impl__(self, other_var):
                 if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
             else:
-                raise TypeError(
-                    "Only supports scalar operations of `int` and `float` now.")
+                # do nothing
+                pass
 
             # 2. scalar method selected
             # here use `scale` replace `elementwise` to get better performance
diff --git a/python/paddle/fluid/layers/math_op_patch.py b/python/paddle/fluid/layers/math_op_patch.py
index 7fde3632753460..a0493530017809 100644
--- a/python/paddle/fluid/layers/math_op_patch.py
+++ b/python/paddle/fluid/layers/math_op_patch.py
@@ -229,8 +229,8 @@ def __impl__(self, other_var):
                 if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
             else:
-                raise TypeError(
-                    "Only supports scalar operations of `int` and `float` now.")
+                # do nothing
+                pass
 
             # 2. scalar method selected
             # here use `scale` replace `elementwise` to get better performance
diff --git a/tools/__pycache__/static_mode_white_list.cpython-35.pyc b/tools/__pycache__/static_mode_white_list.cpython-35.pyc
new file mode 100644
index 0000000000000000000000000000000000000000..5503b0329783028fd00f7a70097cf4b944749f3f
GIT binary patch
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HcmV?d00001


From c8b64850eb6f639e98fe73bcf6c2346e29baeffa Mon Sep 17 00:00:00 2001
From: Chen Weihang <chenweihang@baidu.com>
Date: Thu, 29 Oct 2020 04:45:37 +0000
Subject: [PATCH 3/6] fix scalar method error

---
 python/paddle/fluid/dygraph/math_op_patch.py | 20 +++++++++++---------
 python/paddle/fluid/layers/math_op_patch.py  | 18 ++++++++++--------
 2 files changed, 21 insertions(+), 17 deletions(-)

diff --git a/python/paddle/fluid/dygraph/math_op_patch.py b/python/paddle/fluid/dygraph/math_op_patch.py
index 8ee5e66025c9e4..9c2036ccf72dd3 100644
--- a/python/paddle/fluid/dygraph/math_op_patch.py
+++ b/python/paddle/fluid/dygraph/math_op_patch.py
@@ -162,6 +162,10 @@ def __impl__(self, other_var):
                 # in all cases(+, -, *, /, **, //, %), we need cast tensor.dtype to float
                 if self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
+                # here use `scale` replace `elementwise` to get better performance
+                # but only +, -, *, / can use this method
+                if scalar_method is not None:
+                    return scalar_method(self, other_var)
             elif isinstance(other_var, int):
                 # in all cases(+, -, *, /, **, //, %), we can cast it to float
                 # because the output tensor.dtype depend on the type of input tensor
@@ -169,17 +173,15 @@ def __impl__(self, other_var):
                 # division is a special case
                 if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
+                # here use `scale` replace `elementwise` to get better performance
+                # but only +, -, *, / can use this method
+                if scalar_method is not None:
+                    return scalar_method(self, other_var)
             else:
                 # do nothing
                 pass
 
-            # 2. scalar method selected
-            # here use `scale` replace `elementwise` to get better performance
-            # but only +, -, *, / can use this method
-            if scalar_method is not None:
-                return scalar_method(self, other_var)
-
-            # 3. create varbase for scalar
+            # 2. create varbase for scalar
             lhs_dtype = self.dtype
             if not isinstance(other_var, core.VarBase):
                 if reverse:
@@ -189,7 +191,7 @@ def __impl__(self, other_var):
                     # add fill_op 
                     other_var = create_scalar(value=other_var, dtype=lhs_dtype)
 
-            # 4. unify right var type to left var
+            # 3. unify right var type to left var
             rhs_dtype = other_var.dtype
             if lhs_dtype != rhs_dtype:
                 other_var = astype(other_var, lhs_dtype)
@@ -198,7 +200,7 @@ def __impl__(self, other_var):
                 self = other_var
                 other_var = tmp
 
-            # 5. calculation
+            # 4. calculation
             axis = -1
             math_op = getattr(core.ops, op_type)
             return math_op(self, other_var, 'axis', axis)
diff --git a/python/paddle/fluid/layers/math_op_patch.py b/python/paddle/fluid/layers/math_op_patch.py
index a0493530017809..845aa6365c312a 100644
--- a/python/paddle/fluid/layers/math_op_patch.py
+++ b/python/paddle/fluid/layers/math_op_patch.py
@@ -221,6 +221,10 @@ def __impl__(self, other_var):
                 # in all cases(+, -, *, /, **, //, %), we need cast tensor.dtype to float
                 if self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
+                # here use `scale` replace `elementwise` to get better performance
+                # but only +, -, *, / can use this method
+                if scalar_method is not None:
+                    return scalar_method(self, other_var)
             elif isinstance(other_var, int):
                 # in all cases(+, -, *, /, **, //, %), we can cast it to float
                 # because the output tensor.dtype depend on the type of input tensor
@@ -228,17 +232,15 @@ def __impl__(self, other_var):
                 # division is a special case
                 if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
+                # here use `scale` replace `elementwise` to get better performance
+                # but only +, -, *, / can use this method
+                if scalar_method is not None:
+                    return scalar_method(self, other_var)
             else:
                 # do nothing
                 pass
 
-            # 2. scalar method selected
-            # here use `scale` replace `elementwise` to get better performance
-            # but only +, -, *, / can use this method
-            if scalar_method is not None:
-                return scalar_method(self, other_var)
-
-            # 3. create variable for scalar
+            # 2. create variable for scalar
             lhs_dtype = safe_get_dtype(self)
             if not isinstance(other_var, Variable):
                 if reverse:
@@ -261,7 +263,7 @@ def __impl__(self, other_var):
                     other_var = create_scalar(
                         current_block(self), value=other_var, dtype=lhs_dtype)
 
-            # 4. unify right var type to left var
+            # 3. unify right var type to left var
             rhs_dtype = safe_get_dtype(other_var)
             if lhs_dtype != rhs_dtype:
                 other_var = astype(other_var, lhs_dtype)

From e76b4741a0402ff7777ded64475d844d1b4e5240 Mon Sep 17 00:00:00 2001
From: Chen Weihang <chenweihang@baidu.com>
Date: Thu, 29 Oct 2020 07:26:49 +0000
Subject: [PATCH 4/6] fix test_math_op_path unittest

---
 python/paddle/fluid/dygraph/math_op_patch.py              | 6 ++++++
 python/paddle/fluid/layers/math_op_patch.py               | 6 ++++++
 python/paddle/fluid/tests/unittests/test_math_op_patch.py | 8 ++++++--
 3 files changed, 18 insertions(+), 2 deletions(-)

diff --git a/python/paddle/fluid/dygraph/math_op_patch.py b/python/paddle/fluid/dygraph/math_op_patch.py
index 9c2036ccf72dd3..203a5e0f86ac5b 100644
--- a/python/paddle/fluid/dygraph/math_op_patch.py
+++ b/python/paddle/fluid/dygraph/math_op_patch.py
@@ -171,6 +171,12 @@ def __impl__(self, other_var):
                 # because the output tensor.dtype depend on the type of input tensor
                 other_var = float(other_var)
                 # division is a special case
+                # NOTE(chenweihang): because we cast tensor to float32 instead float64,
+                # the division result can only guarantee the numerical accuracy of 6 digits 
+                # after the decimal point. The result of numpy calculation is of float64 type, 
+                # so the calculation result here and the calculation result of numpy are 
+                # different after 6 decimal point. If necessary, we can also use float64 here.
+                # torch's behavior here is consistent with ours
                 if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
                 # here use `scale` replace `elementwise` to get better performance
diff --git a/python/paddle/fluid/layers/math_op_patch.py b/python/paddle/fluid/layers/math_op_patch.py
index 845aa6365c312a..8f5fdf52d95ef9 100644
--- a/python/paddle/fluid/layers/math_op_patch.py
+++ b/python/paddle/fluid/layers/math_op_patch.py
@@ -230,6 +230,12 @@ def __impl__(self, other_var):
                 # because the output tensor.dtype depend on the type of input tensor
                 other_var = float(other_var)
                 # division is a special case
+                # NOTE(chenweihang): because we cast tensor to float32 instead float64,
+                # the division result can only guarantee the numerical accuracy of 6 digits 
+                # after the decimal point. The result of numpy calculation is of float64 type, 
+                # so the calculation result here and the calculation result of numpy are 
+                # different after 6 decimal point. If necessary, we can also use float64 here.
+                # torch's behavior here is consistent with ours
                 if op_type == 'elementwise_div' and self.dtype in _supported_int_dtype_:
                     self = astype(self, 'float32')
                 # here use `scale` replace `elementwise` to get better performance
diff --git a/python/paddle/fluid/tests/unittests/test_math_op_patch.py b/python/paddle/fluid/tests/unittests/test_math_op_patch.py
index f6eff22d6ce5f0..eec81b7f8fe4df 100644
--- a/python/paddle/fluid/tests/unittests/test_math_op_patch.py
+++ b/python/paddle/fluid/tests/unittests/test_math_op_patch.py
@@ -16,11 +16,15 @@
 
 import unittest
 from decorator_helper import prog_scope
+import paddle
 import paddle.fluid as fluid
 import numpy
 
 
 class TestMathOpPatches(unittest.TestCase):
+    def setUp(self):
+        paddle.enable_static()
+
     @prog_scope()
     def test_add_scalar(self):
         a = fluid.layers.data(name="a", shape=[1])
@@ -197,8 +201,8 @@ def test_integer_div(self):
                         feed={"a": a_np},
                         fetch_list=[b])
 
-        b_np_actual = (a_np / 7).astype('int64')
-        self.assertTrue(numpy.array_equal(b_np, b_np_actual))
+        b_np_actual = (a_np / 7).astype('float32')
+        self.assertTrue(numpy.allclose(b_np, b_np_actual))
 
     @prog_scope()
     def test_equal(self):

From 818880fc2bf2afbbfd28fea4060a3f32e60c0df2 Mon Sep 17 00:00:00 2001
From: Chen Weihang <chenweihang@baidu.com>
Date: Thu, 29 Oct 2020 08:27:31 +0000
Subject: [PATCH 5/6] add future division for unittest

---
 python/paddle/fluid/tests/unittests/test_math_op_patch.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/python/paddle/fluid/tests/unittests/test_math_op_patch.py b/python/paddle/fluid/tests/unittests/test_math_op_patch.py
index eec81b7f8fe4df..76e371b216778f 100644
--- a/python/paddle/fluid/tests/unittests/test_math_op_patch.py
+++ b/python/paddle/fluid/tests/unittests/test_math_op_patch.py
@@ -12,7 +12,7 @@
 # See the License for the specific language governing permissions and
 # limitations under the License.
 
-from __future__ import print_function
+from __future__ import print_function, division
 
 import unittest
 from decorator_helper import prog_scope

From 964799c6706ba8016260242db30050ec31d5a776 Mon Sep 17 00:00:00 2001
From: Chen Weihang <chenweihang@baidu.com>
Date: Fri, 30 Oct 2020 07:33:44 +0000
Subject: [PATCH 6/6] rm useless bin file

---
 .../static_mode_white_list.cpython-35.pyc       | Bin 19105 -> 0 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 delete mode 100644 tools/__pycache__/static_mode_white_list.cpython-35.pyc

diff --git a/tools/__pycache__/static_mode_white_list.cpython-35.pyc b/tools/__pycache__/static_mode_white_list.cpython-35.pyc
deleted file mode 100644
index 5503b0329783028fd00f7a70097cf4b944749f3f..0000000000000000000000000000000000000000
GIT binary patch
literal 0
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