wehub-resource-sync
302 lines
13 KiB
Python
302 lines
13 KiB
Python
# 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.
|
|
|
|
import unittest
|
|
|
|
import numpy as np
|
|
from op_test import get_device_place, is_custom_device
|
|
|
|
import paddle
|
|
|
|
|
|
# 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 = get_device_place()
|
|
|
|
def test_static_api(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
# results are from [-100, 100).
|
|
x_bool = paddle.static.data(
|
|
name="x_bool", shape=[10, 12], dtype="bool"
|
|
)
|
|
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=-10, high=10, dtype=dtype)
|
|
for dtype in self.dtype
|
|
]
|
|
outs1 = exe.run(feed={'x_bool': self.x_bool}, fetch_list=[outlist1])
|
|
for out, dtype in zip(outs1, self.dtype):
|
|
self.assertTrue(out.dtype, np.dtype(dtype))
|
|
self.assertTrue(((out >= -10) & (out <= 10)).all(), True)
|
|
paddle.disable_static()
|
|
|
|
def test_static_api_with_int32(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_int32 = paddle.static.data(
|
|
name="x_int32", shape=[10, 12], dtype="int32"
|
|
)
|
|
exe = paddle.static.Executor(self.place)
|
|
# x dtype is int32 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
|
|
outlist2 = [
|
|
paddle.randint_like(x_int32, low=-5, high=10, dtype=dtype)
|
|
for dtype in self.dtype
|
|
]
|
|
outs2 = exe.run(
|
|
paddle.static.default_main_program(),
|
|
feed={'x_int32': np.zeros((10, 12)).astype(np.int32)},
|
|
fetch_list=[outlist2],
|
|
)
|
|
for out2, dtype in zip(outs2, self.dtype):
|
|
self.assertTrue(out2.dtype, np.dtype(dtype))
|
|
self.assertTrue(((out2 >= -5) & (out2 <= 10)).all(), True)
|
|
paddle.disable_static()
|
|
|
|
def test_static_api_with_int64(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_int64 = paddle.static.data(
|
|
name="x_int64", shape=[10, 12], dtype="int64"
|
|
)
|
|
exe = paddle.static.Executor(self.place)
|
|
# 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)
|
|
for out, dtype in zip(outs3, self.dtype):
|
|
self.assertTrue(out.dtype, np.dtype(dtype))
|
|
self.assertTrue(((out >= -100) & (out <= 100)).all(), True)
|
|
paddle.disable_static()
|
|
|
|
def test_static_api_with_fp16(self):
|
|
paddle.enable_static()
|
|
if paddle.is_compiled_with_cuda() or is_custom_device():
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_float16 = paddle.static.data(
|
|
name="x_float16", shape=[10, 12], dtype="float16"
|
|
)
|
|
exe = paddle.static.Executor(self.place)
|
|
# x dtype is float16 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
|
|
outlist4 = [
|
|
paddle.randint_like(x_float16, low=-3, high=25, dtype=dtype)
|
|
for dtype in self.dtype
|
|
]
|
|
outs4 = exe.run(
|
|
feed={'x_float16': self.x_float16}, fetch_list=outlist4
|
|
)
|
|
for out, dtype in zip(outs4, self.dtype):
|
|
self.assertTrue(out.dtype, np.dtype(dtype))
|
|
self.assertTrue(((out >= -3) & (out <= 25)).all(), True)
|
|
paddle.disable_static()
|
|
|
|
def test_static_api_with_float32(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_float32 = paddle.static.data(
|
|
name="x_float32", shape=[10, 12], dtype="float32"
|
|
)
|
|
exe = paddle.static.Executor(self.place)
|
|
# x dtype is float32 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
|
|
outlist5 = [
|
|
paddle.randint_like(x_float32, low=-25, high=25, dtype=dtype)
|
|
for dtype in self.dtype
|
|
]
|
|
outs5 = exe.run(
|
|
feed={'x_float32': self.x_float32}, fetch_list=outlist5
|
|
)
|
|
for out, dtype in zip(outs5, self.dtype):
|
|
self.assertTrue(out.dtype, np.dtype(dtype))
|
|
self.assertTrue(((out >= -25) & (out <= 25)).all(), True)
|
|
paddle.disable_static()
|
|
|
|
def test_static_api_with_float64(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_float64 = paddle.static.data(
|
|
name="x_float64", shape=[10, 12], dtype="float64"
|
|
)
|
|
exe = paddle.static.Executor(self.place)
|
|
# x dtype is float64 output dtype in ["bool", "int32", "int64", "float16", "float32", "float64"]
|
|
outlist6 = [
|
|
paddle.randint_like(x_float64, low=-16, high=16, dtype=dtype)
|
|
for dtype in self.dtype
|
|
]
|
|
outs6 = exe.run(
|
|
feed={'x_float64': self.x_float64}, fetch_list=outlist6
|
|
)
|
|
for out, dtype in zip(outs6, self.dtype):
|
|
self.assertTrue(out.dtype, dtype)
|
|
self.assertTrue(((out >= -16) & (out <= 16)).all(), True)
|
|
paddle.disable_static()
|
|
|
|
def test_dygraph_api(self):
|
|
paddle.disable_static(self.place)
|
|
# x dtype ["bool", "int32", "int64", "float32", "float64"]
|
|
for x in [
|
|
self.x_bool,
|
|
self.x_int32,
|
|
self.x_int64,
|
|
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
|
|
)
|
|
self.assertTrue(out.numpy().dtype, np.dtype(dtype))
|
|
self.assertTrue(
|
|
((out.numpy() >= -100) & (out.numpy() <= 100)).all(), True
|
|
)
|
|
# x dtype ["float16"]
|
|
if paddle.is_compiled_with_cuda() or is_custom_device():
|
|
x_inputs = paddle.to_tensor(self.x_float16)
|
|
# 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
|
|
)
|
|
self.assertTrue(out.numpy().dtype, np.dtype(dtype))
|
|
self.assertTrue(
|
|
((out.numpy() >= -100) & (out.numpy() <= 100)).all(), True
|
|
)
|
|
paddle.enable_static()
|
|
|
|
def test_errors(self):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(
|
|
paddle.static.Program(), paddle.static.Program()
|
|
):
|
|
x_bool = paddle.static.data(
|
|
name="x_bool", shape=[10, 12], dtype="bool"
|
|
)
|
|
x_int32 = paddle.static.data(
|
|
name="x_int32", shape=[10, 12], dtype="int32"
|
|
)
|
|
x_int64 = paddle.static.data(
|
|
name="x_int64", shape=[10, 12], dtype="int64"
|
|
)
|
|
x_float16 = paddle.static.data(
|
|
name="x_float16", shape=[10, 12], dtype="float16"
|
|
)
|
|
x_float32 = paddle.static.data(
|
|
name="x_float32", shape=[10, 12], dtype="float32"
|
|
)
|
|
x_float64 = paddle.static.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
|
|
if paddle.is_compiled_with_cuda() or is_custom_device():
|
|
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()
|