Add yaml for randint OP (#41375)

paddle/phi/infermeta/nullary.cc

@@ -63,6 +63,34 @@ void RandpermInferMeta(int n, DataType dtype, MetaTensor* out) {
   out->set_dtype(dtype);
 }
 
+void RandintInferMeta(
+    int low, int high, const IntArray& shape, DataType dtype, MetaTensor* out) {
+  PADDLE_ENFORCE_NOT_NULL(
+      out, errors::InvalidArgument("Output(Out) of RandintOp is null."));
+  PADDLE_ENFORCE_LT(
+      low,
+      high,
+      errors::InvalidArgument("randint's low must less then high, "
+                              "but received: low = %d, high = %d.",
+                              low,
+                              high));
+
+  auto& shape_vector = shape.GetData();
+  PADDLE_ENFORCE_EQ(
+      shape_vector.empty(),
+      false,
+      errors::InvalidArgument("The shape information should not be empty, it "
+                              "must be set by Attr(shape)."));
+
+  std::vector<int64_t> tensor_shape;
+  tensor_shape.reserve(shape_vector.size());
+  for (auto dim : shape_vector) {
+    tensor_shape.push_back(static_cast<int64_t>(dim));
+  }
+  out->set_dims(make_ddim(tensor_shape));
+  out->set_dtype(dtype);
+}
+
 void TruncatedGaussianRandomInferMeta(const std::vector<int>& shape,
                                       float mean,
                                       float std,

paddle/phi/infermeta/nullary.h

@@ -55,6 +55,9 @@ void GaussianRandomInferMeta(const IntArray& shape,
 
 void RandpermInferMeta(int n, DataType dtype, MetaTensor* out);
 
+void RandintInferMeta(
+    int low, int high, const IntArray& shape, DataType dtype, MetaTensor* out);
+
 void TruncatedGaussianRandomInferMeta(const std::vector<int>& shape,
                                       float mean,
                                       float std,

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

@@ -14,13 +14,14 @@
 
 from __future__ import print_function
 
+import os
+import paddle
 import unittest
 import numpy as np
 from op_test import OpTest
-import paddle
 from paddle.fluid import core
+from paddle.fluid.framework import _test_eager_guard
 from paddle.static import program_guard, Program
-import os
 
 paddle.enable_static()
 
@@ -53,6 +54,10 @@ class TestRandintOp(OpTest):
             np.allclose(
                 hist, prob, rtol=0, atol=0.001), "hist: " + str(hist))
 
+    def test_check_output_eager(self):
+        with _test_eager_guard():
+            self.test_check_output()
+
 
 class TestRandintOpError(unittest.TestCase):
     def test_errors(self):
@@ -67,6 +72,10 @@ class TestRandintOpError(unittest.TestCase):
             self.assertRaises(
                 TypeError, paddle.randint, 5, shape=[shape_tensor])
 
+    def test_errors_eager(self):
+        with _test_eager_guard():
+            self.test_errors()
+
 
 class TestRandintOp_attr_tensorlist(OpTest):
     def setUp(self):
@@ -93,6 +102,10 @@ class TestRandintOp_attr_tensorlist(OpTest):
             np.allclose(
                 hist, prob, rtol=0, atol=0.001), "hist: " + str(hist))
 
+    def test_check_output_eager(self):
+        with _test_eager_guard():
+            self.test_check_output()
+
 
 class TestRandint_attr_tensor(OpTest):
     def setUp(self):
@@ -114,6 +127,10 @@ class TestRandint_attr_tensor(OpTest):
             np.allclose(
                 hist, prob, rtol=0, atol=0.001), "hist: " + str(hist))
 
+    def test_check_output_eager(self):
+        with _test_eager_guard():
+            self.test_check_output()
+
 
 # Test python API
 class TestRandintAPI(unittest.TestCase):
@@ -145,18 +162,30 @@ class TestRandintAPI(unittest.TestCase):
                 feed={'var_shape': np.array([100, 100]).astype('int64')},
                 fetch_list=[out1, out2, out3, out4, out5])
 
+    def test_api_eager(self):
+        with _test_eager_guard():
+            self.test_api()
+
 
 class TestRandintImperative(unittest.TestCase):
     def test_api(self):
-        n = 10
         paddle.disable_static()
+
+        self.run_test_case()
+
+        with _test_eager_guard():
+            self.run_test_case()
+
+        paddle.enable_static()
+
+    def run_test_case(self):
+        n = 10
         x1 = paddle.randint(n, shape=[10], dtype="int32")
         x2 = paddle.tensor.randint(n)
         x3 = paddle.tensor.random.randint(n)
         for i in [x1, x2, x3]:
             for j in i.numpy().tolist():
                 self.assertTrue((j >= 0 and j < n))
-        paddle.enable_static()
 
 
 class TestRandomValue(unittest.TestCase):
@@ -174,6 +203,15 @@ class TestRandomValue(unittest.TestCase):
 
         print("Test Fixed Random number on GPU------>")
         paddle.disable_static()
+
+        self.run_test_case()
+
+        with _test_eager_guard():
+            self.run_test_case()
+
+        paddle.enable_static()
+
+    def run_test_case(self):
         paddle.set_device('gpu')
         paddle.seed(100)
 
@@ -198,7 +236,6 @@ class TestRandomValue(unittest.TestCase):
         self.assertTrue(np.array_equal(x[20, 1, 600, 600:605], expect))
         expect = [3581, 3420, -8027, -5237, -2436]
         self.assertTrue(np.array_equal(x[30, 2, 1000, 1000:1005], expect))
-        paddle.enable_static()
 
 
 if __name__ == "__main__":

python/paddle/tensor/random.py

@@ -22,7 +22,7 @@ from ..fluid.layers import utils
 import paddle
 from paddle import _C_ops
 from paddle.static import Variable
-from ..fluid.framework import _in_legacy_dygraph, in_dygraph_mode
+from paddle.fluid.framework import in_dygraph_mode, _in_legacy_dygraph, _current_expected_place
 
 __all__ = []
 
@@ -687,7 +687,11 @@ def randint(low=0, high=None, shape=[1], dtype=None, name=None):
     if not isinstance(dtype, core.VarDesc.VarType):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
-    if paddle.in_dynamic_mode():
+    if in_dygraph_mode():
+        shape = utils.convert_shape_to_list(shape)
+        place = _current_expected_place()
+        return _C_ops.final_state_randint(low, high, shape, dtype, place)
+    if _in_legacy_dygraph():
         shape = utils.convert_shape_to_list(shape)
         return _C_ops.randint('shape', shape, 'low', low, 'high', high, 'seed',
                               0, 'dtype', dtype)
@@ -920,8 +924,7 @@ def randperm(n, dtype="int64", name=None):
         dtype = convert_np_dtype_to_dtype_(dtype)
 
     if in_dygraph_mode():
-        return _C_ops.final_state_randperm(
-            n, dtype, paddle.fluid.framework._current_expected_place())
+        return _C_ops.final_state_randperm(n, dtype, _current_expected_place())
     if _in_legacy_dygraph():
         return _C_ops.randperm('n', n, 'seed', 0, 'dtype', dtype)
 

python/paddle/utils/code_gen/api.yaml

@@ -1265,6 +1265,18 @@
     data_type : x
   backward : put_along_axis_grad
 
+- api : randint
+  args : (int low, int high, IntArray shape, DataType dtype=DataType::INT64, Place place={})
+  output : Tensor(out)
+  infer_meta :
+    func : RandintInferMeta
+    param : [low, high, shape, dtype]
+  kernel :
+    func : randint
+    param : [low, high, shape, dtype]
+    data_type : dtype
+    backend : place
+
 - api : randperm
   args : (int n, DataType dtype, Place place={})
   output : Tensor
@@ -1276,7 +1288,7 @@
     param : [n, dtype]
     data_type : dtype
     backend : place
-
+                   
 - api : reciprocal
   args : (Tensor x)
   output : Tensor