[PaddlePaddle hackathon] Add randint_like

python/paddle/__init__.py

@@ -228,6 +228,7 @@
 from .tensor.random import randn  # noqa: F401
 from .tensor.random import rand  # noqa: F401
 from .tensor.random import randint  # noqa: F401
+from .tensor.random import randint_like  # noqa: F401
 from .tensor.random import randperm  # noqa: F401
 from .tensor.search import argmax  # noqa: F401
 from .tensor.search import argmin  # noqa: F401
@@ -373,6 +374,7 @@
            'ParamAttr',
            'stanh',
            'randint',
+           'randint_like',
            'assign',
            'gather',
            'scale',

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

@@ -0,0 +1,199 @@
+# 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.
+
+from __future__ import print_function
+
+import unittest
+import numpy as np
+import paddle
+from paddle.static import program_guard, Program
+
+
+# Test python API
+class TestRandintLikeAPI(unittest.TestCase):
+    def setUp(self):
+        self.x_bool = np.zeros((10, 12)).astype("bool")
+        self.x_int32 = np.zeros((10, 12)).astype("int32")
+        self.x_int64 = np.zeros((10, 12)).astype("int64")
+        self.x_float16 = np.zeros((10, 12)).astype("float16")
+        self.x_float32 = np.zeros((10, 12)).astype("float32")
+        self.x_float64 = np.zeros((10, 12)).astype("float64")
+
+        self.dtype = ["bool", "int32", "int64", "float16", "float32", "float64"]
+        self.place=paddle.CUDAPlace(0) if paddle.is_compiled_with_cuda() \
+            else paddle.CPUPlace()
+
+    def test_static_api(self):
+        paddle.enable_static()
+        with program_guard(Program(), Program()):
+            # results are from [-100, 100).
+            x_bool = paddle.fluid.data(
+                name="x_bool", shape=[10, 12], dtype="bool")
+            x_int32 = paddle.fluid.data(
+                name="x_int32", shape=[10, 12], dtype="int32")
+            x_int64 = paddle.fluid.data(
+                name="x_int64", shape=[10, 12], dtype="int64")
+            x_float16 = paddle.fluid.data(
+                name="x_float16", shape=[10, 12], dtype="float16")
+            x_float32 = paddle.fluid.data(
+                name="x_float32", shape=[10, 12], dtype="float32")
+            x_float64 = paddle.fluid.data(
+                name="x_float64", shape=[10, 12], dtype="float64")
+
+            exe = paddle.static.Executor(self.place)
+
+            # x dtype is bool output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
+            outlist1 = [
+                paddle.randint_like(
+                    x_bool, low=-100, high=100, dtype=dtype)
+                for dtype in self.dtype
+            ]
+            outs1 = exe.run(feed={'x_bool': self.x_bool}, fetch_list=outlist1)
+
+            # x dtype is int32 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
+            outlist2 = [
+                paddle.randint_like(
+                    x_int32, low=-100, high=100, dtype=dtype)
+                for dtype in self.dtype
+            ]
+            outs2 = exe.run(feed={'x_int32': self.x_int32}, fetch_list=outlist2)
+
+            # x dtype is int64 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
+            outlist3 = [
+                paddle.randint_like(
+                    x_int64, low=-100, high=100, dtype=dtype)
+                for dtype in self.dtype
+            ]
+            outs3 = exe.run(feed={'x_int64': self.x_int64}, fetch_list=outlist3)
+
+            # x dtype is float16 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
+            outlist4 = [
+                paddle.randint_like(
+                    x_float16, low=-100, high=100, dtype=dtype)
+                for dtype in self.dtype
+            ]
+            outs4 = exe.run(feed={'x_float16': self.x_float16},
+                            fetch_list=outlist4)
+
+            # x dtype is float32 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
+            outlist5 = [
+                paddle.randint_like(
+                    x_float32, low=-100, high=100, dtype=dtype)
+                for dtype in self.dtype
+            ]
+            outs5 = exe.run(feed={'x_float32': self.x_float32},
+                            fetch_list=outlist5)
+
+            # x dtype is float64 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
+            outlist6 = [
+                paddle.randint_like(
+                    x_float64, low=-100, high=100, dtype=dtype)
+                for dtype in self.dtype
+            ]
+            outs6 = exe.run(feed={'x_float64': self.x_float64},
+                            fetch_list=outlist6)
+
+    def test_dygraph_api(self):
+        paddle.disable_static(self.place)
+        # x dtype ["bool", "int32", "int64", "float16", "float32", "float64"]
+        for x in [
+                self.x_bool, self.x_int32, self.x_int64, self.x_float16,
+                self.x_float32, self.x_float64
+        ]:
+            x_inputs = paddle.to_tensor(x)
+            # self.dtype ["bool", "int32", "int64", "float16", "float32", "float64"]
+            for dtype in self.dtype:
+                out = paddle.randint_like(
+                    x_inputs, low=-100, high=100, dtype=dtype)
+        paddle.enable_static()
+
+    def test_errors(self):
+        paddle.enable_static()
+        with program_guard(Program(), Program()):
+            x_bool = paddle.fluid.data(
+                name="x_bool", shape=[10, 12], dtype="bool")
+            x_int32 = paddle.fluid.data(
+                name="x_int32", shape=[10, 12], dtype="int32")
+            x_int64 = paddle.fluid.data(
+                name="x_int64", shape=[10, 12], dtype="int64")
+            x_float16 = paddle.fluid.data(
+                name="x_float16", shape=[10, 12], dtype="float16")
+            x_float32 = paddle.fluid.data(
+                name="x_float32", shape=[10, 12], dtype="float32")
+            x_float64 = paddle.fluid.data(
+                name="x_float64", shape=[10, 12], dtype="float64")
+
+            # x dtype is bool
+            # low is 5 and high is 5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_bool, low=5, high=5)
+            # low(default value) is 0 and high is -5, low must less then high
+            self.assertRaises(ValueError, paddle.randint_like, x_bool, high=-5)
+            # if high is None, low must be greater than 0
+            self.assertRaises(ValueError, paddle.randint_like, x_bool, low=-5)
+
+            # x dtype is int32
+            # low is 5 and high is 5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_int32, low=5, high=5)
+            # low(default value) is 0 and high is -5, low must less then high
+            self.assertRaises(ValueError, paddle.randint_like, x_int32, high=-5)
+            # if high is None, low must be greater than 0
+            self.assertRaises(ValueError, paddle.randint_like, x_int32, low=-5)
+
+            # x dtype is int64
+            # low is 5 and high is 5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_int64, low=5, high=5)
+            # low(default value) is 0 and high is -5, low must less then high
+            self.assertRaises(ValueError, paddle.randint_like, x_int64, high=-5)
+            # if high is None, low must be greater than 0
+            self.assertRaises(ValueError, paddle.randint_like, x_int64, low=-5)
+
+            # x dtype is float16
+            # low is 5 and high is 5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float16, low=5, high=5)
+            # low(default value) is 0 and high is -5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float16, high=-5)
+            # if high is None, low must be greater than 0
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float16, low=-5)
+
+            # x dtype is float32
+            # low is 5 and high is 5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float32, low=5, high=5)
+            # low(default value) is 0 and high is -5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float32, high=-5)
+            # if high is None, low must be greater than 0
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float32, low=-5)
+
+            # x dtype is float64
+            # low is 5 and high is 5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float64, low=5, high=5)
+            # low(default value) is 0 and high is -5, low must less then high
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float64, high=-5)
+            # if high is None, low must be greater than 0
+            self.assertRaises(
+                ValueError, paddle.randint_like, x_float64, low=-5)
+
+
+if __name__ == "__main__":
+    unittest.main()

python/paddle/tensor/__init__.py

@@ -195,6 +195,7 @@
 from .random import randn  # noqa: F401
 from .random import rand  # noqa: F401
 from .random import randint  # noqa: F401
+from .random import randint_like  # noqa: F401
 from .random import randperm  # noqa: F401
 from .search import argmax  # noqa: F401
 from .search import argmin  # noqa: F401