diff --git a/oneflow/python/test/modules/automated_test_util.py b/oneflow/python/test/modules/automated_test_util.py
index 6826e0fe33678e3c1eeb73977f4f03906713fb62..0459756ab4acd4b02673c3d317a345be76428956 100644
--- a/oneflow/python/test/modules/automated_test_util.py
+++ b/oneflow/python/test/modules/automated_test_util.py
@@ -220,6 +220,10 @@ def test_against_pytorch(
if rng.random() < 1 / 3:
continue
flow_data, torch_data = generate(name)
+ if isinstance(torch_data, torch.Tensor):
+ torch_data = torch_data.to(device)
+ if isinstance(flow_data, flow.Tensor):
+ flow_data = flow_data.to(device)
flow_attr_dict[name] = flow_data
torch_attr_dict[name] = torch_data
@@ -291,7 +295,7 @@ def test_against_pytorch(
)
test_case.assertTrue(
is_allclose,
- f"flow_tensor = {flow_tensor},\ntorch_tensor = {torch_tensor},\nattr_dict = {torch_attr_dict}",
+ f"flow_tensor = {flow_tensor},\ntorch_tensor = {torch_tensor},\nattr_dict = {torch_attr_dict},\nflow_input_tensor = {flow_input_original}",
)
allclose_or_fail(flow_res, torch_res)
diff --git a/oneflow/python/test/modules/test_activation.py b/oneflow/python/test/modules/test_activation.py
index a55fb54ae9f4226cbbb76795f05fddfcbb6ced45..28c6aefdc74e51d034f84a057540730b00ed1f18 100644
--- a/oneflow/python/test/modules/test_activation.py
+++ b/oneflow/python/test/modules/test_activation.py
@@ -214,6 +214,16 @@ class TestELUModule(flow.unittest.TestCase):
for arg in GenArgList(arg_dict):
_test_elu_function_impl(test_case, *arg)
+ def test_elu_module_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_module_against_pytorch(
+ test_case,
+ "nn.ELU",
+ extra_annotations={"alpha": float},
+ extra_generators={"alpha": random(0, 6)},
+ device=device,
+ )
+
def _np_gelu(x):
return 0.5 * x * (1 + special.erf(x / np.sqrt(2)))
@@ -693,6 +703,17 @@ class TestSoftplusModule(flow.unittest.TestCase):
for arg in GenArgList(arg_dict):
arg[0](test_case, *arg[1:])
+ @unittest.skip("Pytorch Softplus has bug")
+ def test_softplus_module_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_module_against_pytorch(
+ test_case,
+ "nn.Softplus",
+ extra_annotations={"beta": int, "threshold": int},
+ extra_generators={"beta": random(3, 4), "threshold": random(1, 2)},
+ device=device,
+ )
+
def _test_hardswish_impl(test_case, shape, device):
m = flow.nn.Hardswish()
diff --git a/oneflow/python/test/modules/test_atan2.py b/oneflow/python/test/modules/test_atan2.py
index 0c5d059d22eb49a446860593e58865a1b3f7ecb5..4569275caf6c388b9f990d5d6de0285dfac5da05 100644
--- a/oneflow/python/test/modules/test_atan2.py
+++ b/oneflow/python/test/modules/test_atan2.py
@@ -20,6 +20,7 @@ import numpy as np
from test_util import GenArgList
import oneflow.experimental as flow
+from automated_test_util import *
def _test_atan2_forward(test_case, shape, scalar, device):
@@ -120,6 +121,19 @@ class TestAtan2(flow.unittest.TestCase):
for arg in GenArgList(arg_dict):
_test_atan2_backward(test_case, *arg)
+ def test_flow_atan2_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_flow_against_pytorch(
+ test_case,
+ "atan2",
+ extra_annotations={"other": flow.Tensor},
+ extra_generators={
+ "input": random_tensor(ndim=1, dim1=1),
+ "other": random_tensor(ndim=1, dim1=1),
+ },
+ device=device,
+ )
+
if __name__ == "__main__":
unittest.main()
diff --git a/oneflow/python/test/modules/test_math_ops.py b/oneflow/python/test/modules/test_math_ops.py
index e1fc340bb6864669579a3b970ec3ff84e02c13e5..39d3331d73dbf0135cb599d1876e813e9651622b 100644
--- a/oneflow/python/test/modules/test_math_ops.py
+++ b/oneflow/python/test/modules/test_math_ops.py
@@ -78,6 +78,47 @@ class TestVariance(flow.unittest.TestCase):
arg[0](test_case, *arg[1:])
+def _test_sinh_impl(test_case, shape, device):
+ np_input = np.random.randn(*shape)
+ of_input = flow.Tensor(
+ np_input, dtype=flow.float32, device=flow.device(device), requires_grad=True
+ )
+
+ np_x_grad = np.cosh(np_input)
+ of_out = flow.sinh(of_input)
+ np_out = np.sinh(np_input)
+ test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
+
+ of_out = of_out.sum()
+ of_out.backward()
+ test_case.assertTrue(np.allclose(of_input.grad.numpy(), np_x_grad, 1e-4, 1e-4))
+
+
+@unittest.skipIf(
+ not flow.unittest.env.eager_execution_enabled(),
+ ".numpy() doesn't work in lazy mode",
+)
+class Testsinh(flow.unittest.TestCase):
+ def test_sinh(test_case):
+ arg_dict = OrderedDict()
+ arg_dict["shape"] = [(2, 3), (2, 4, 5, 6)]
+ arg_dict["device"] = ["cpu", "cuda"]
+ for arg in GenArgList(arg_dict):
+ _test_sinh_impl(test_case, *arg)
+
+ def test_flow_sinh_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_flow_against_pytorch(
+ test_case, "sinh", device=device,
+ )
+
+ def test_flow_tensor_sinh_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_tensor_against_pytorch(
+ test_case, "sinh", device=device,
+ )
+
+
def _test_sin(test_case, shape, device):
input = flow.Tensor(np.random.randn(*shape), device=flow.device(device))
of_out = flow.sin(input)
@@ -522,6 +563,30 @@ class TestAsinh(flow.unittest.TestCase):
_test_asinh(test_case, *arg)
_test_arcsinh(test_case, *arg)
+ def test_flow_asinh_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_flow_against_pytorch(
+ test_case, "asinh", device=device,
+ )
+
+ def test_flow_arcsinh_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_flow_against_pytorch(
+ test_case, "arcsinh", device=device,
+ )
+
+ def test_flow_tensor_asinh_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_tensor_against_pytorch(
+ test_case, "asinh", device=device,
+ )
+
+ def test_flow_tensor_arcsinh_with_random_data(test_case):
+ for device in ["cpu", "cuda"]:
+ test_tensor_against_pytorch(
+ test_case, "arcsinh", device=device,
+ )
+
def _topk_np(input, k, dim: int = None, largest: bool = True, _sorted: bool = True):
in_dims = input.shape
diff --git a/oneflow/python/test/modules/test_sinh.py b/oneflow/python/test/modules/test_sinh.py
deleted file mode 100644
index c142faee5f2117107470b0f4c6aa568f83611a55..0000000000000000000000000000000000000000
--- a/oneflow/python/test/modules/test_sinh.py
+++ /dev/null
@@ -1,55 +0,0 @@
-"""
-Copyright 2020 The OneFlow 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
-from collections import OrderedDict
-
-import numpy as np
-
-from test_util import GenArgList
-import oneflow.experimental as flow
-
-
-def _test_sinh_impl(test_case, shape, device):
- np_input = np.random.randn(*shape)
- of_input = flow.Tensor(
- np_input, dtype=flow.float32, device=flow.device(device), requires_grad=True
- )
-
- np_x_grad = np.cosh(np_input)
- of_out = flow.sinh(of_input)
- np_out = np.sinh(np_input)
- test_case.assertTrue(np.allclose(of_out.numpy(), np_out, 1e-4, 1e-4))
-
- of_out = of_out.sum()
- of_out.backward()
- test_case.assertTrue(np.allclose(of_input.grad.numpy(), np_x_grad, 1e-4, 1e-4))
-
-
-@unittest.skipIf(
- not flow.unittest.env.eager_execution_enabled(),
- ".numpy() doesn't work in lazy mode",
-)
-class Testsinh(flow.unittest.TestCase):
- def test_sinh(test_case):
- arg_dict = OrderedDict()
- arg_dict["shape"] = [(2, 3), (2, 4, 5, 6)]
- arg_dict["device"] = ["cpu", "cuda"]
- for arg in GenArgList(arg_dict):
- _test_sinh_impl(test_case, *arg)
-
-
-if __name__ == "__main__":
- unittest.main()