support math operator for variable (#23063)

* support math operator for variable, test=develop

* polish code, test=develop

* polish code, test=develop

python/paddle/fluid/dygraph/math_op_patch.py

@@ -19,6 +19,9 @@ from ..framework import Variable, convert_np_dtype_to_dtype_
 from ..layers.layer_function_generator import OpProtoHolder
 from . import to_variable, no_grad
 
+import numpy as np
+import six
+
 _supported_int_dtype_ = [
     core.VarDesc.VarType.UINT8,
     core.VarDesc.VarType.INT8,
@@ -116,6 +119,43 @@ def monkey_patch_math_varbase():
     def _neg_(var):
         return _scalar_elementwise_op_(var, -1.0, 0.0)
 
+    def _float_(var):
+        numel = np.prod(var.shape)
+        assert numel == 1, "only one element variable can be converted to float."
+        tensor = var.value().get_tensor()
+        assert tensor._is_initialized(), "variable's tensor is not initialized"
+        return float(var.numpy().flatten()[0])
+
+    def _long_(var):
+        numel = np.prod(var.shape)
+        assert numel == 1, "only one element variable can be converted to long."
+        tensor = var.value().get_tensor()
+        assert tensor._is_initialized(), "variable's tensor is not initialized"
+        if six.PY2:
+            return long(var.numpy().flatten()[0])
+        else:
+            return int(var.numpy().flatten()[0])
+
+    def _int_(var):
+        numel = np.prod(var.shape)
+        assert numel == 1, "only one element variable can be converted to int."
+        tensor = var.value().get_tensor()
+        assert tensor._is_initialized(), "variable's tensor is not initialized"
+        return int(var.numpy().flatten()[0])
+
+    def _len_(var):
+        return var.shape[0]
+
+    def _index_(var):
+        numel = np.prod(var.shape)
+        assert numel == 1, "only one element variable can be converted to python index."
+        tensor = var.value().get_tensor()
+        assert tensor._is_initialized(), "variable's tensor is not initialized"
+        if six.PY2:
+            return long(var.numpy().flatten()[0])
+        else:
+            return int(var.numpy().flatten()[0])
+
     def _scalar_elementwise_add_(var, value):
         return _scalar_elementwise_op_(var, 1.0, value)
 
@@ -220,4 +260,9 @@ def monkey_patch_math_varbase():
 
     # b = -a
     core.VarBase.__neg__ = _neg_
+    core.VarBase.__float__ = _float_
+    core.VarBase.__long__ = _long_
+    core.VarBase.__int__ = _int_
+    core.VarBase.__len__ = _len_
+    core.VarBase.__index__ = _index_
     core.VarBase.astype = astype

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

@@ -18,6 +18,7 @@ import unittest
 from decorator_helper import prog_scope
 import paddle.fluid as fluid
 import numpy as np
+import six
 
 
 class TestMathOpPatchesVarBase(unittest.TestCase):
@@ -208,6 +209,34 @@ class TestMathOpPatchesVarBase(unittest.TestCase):
             res = -a
             self.assertTrue(np.array_equal(res.numpy(), -a_np))
 
+    def test_float_int_long(self):
+        with fluid.dygraph.guard():
+            a = fluid.dygraph.to_variable(np.array([100.1]))
+            self.assertTrue(float(a) == 100.1)
+            self.assertTrue(int(a) == 100)
+            if six.PY2:
+                self.assertTrue(long(a) == 100)
+            else:
+                self.assertTrue(int(a) == 100)
+
+    def test_len(self):
+        a_np = np.random.uniform(-1, 1, self.shape).astype(self.dtype)
+        with fluid.dygraph.guard():
+            a = fluid.dygraph.to_variable(a_np)
+            self.assertTrue(len(a) == 10)
+
+    def test_index(self):
+        with fluid.dygraph.guard():
+            var1 = fluid.dygraph.to_variable(np.array([2]))
+            i_tmp = 0
+            for i in range(var1):
+                self.assertTrue(i == i_tmp)
+                i_tmp = i_tmp + 1
+            list1 = [1, 2, 3, 4, 5]
+            self.assertTrue(list1[var1] == 3)
+            str1 = "just test"
+            self.assertTrue(str1[var1] == 's')
+
 
 if __name__ == '__main__':
     unittest.main()