From 2d5d44ab22c80f457bbeb2d391a71a85184c99da Mon Sep 17 00:00:00 2001 From: peixu_ren Date: Wed, 19 Aug 2020 17:07:14 -0400 Subject: [PATCH] Add test cases for uniform ops on GPU --- .../ascend/test_aicpu_ops/test_uniform_int.py | 12 ----- .../test_aicpu_ops/test_uniform_real.py | 12 ----- tests/st/ops/gpu/test_standard_normal.py | 5 +- tests/st/ops/gpu/test_uniform_int.py | 46 +++++++++++++++++++ tests/st/ops/gpu/test_uniform_real.py | 24 +++++----- 5 files changed, 61 insertions(+), 38 deletions(-) create mode 100644 tests/st/ops/gpu/test_uniform_int.py diff --git a/tests/st/ops/ascend/test_aicpu_ops/test_uniform_int.py b/tests/st/ops/ascend/test_aicpu_ops/test_uniform_int.py index 7e84cff5b9..7dbfb1f322 100644 --- a/tests/st/ops/ascend/test_aicpu_ops/test_uniform_int.py +++ b/tests/st/ops/ascend/test_aicpu_ops/test_uniform_int.py @@ -41,15 +41,3 @@ def test_net_1D(): tminval, tmaxval = Tensor(minval, mstype.int32), Tensor(maxval, mstype.int32) output = net(tminval, tmaxval) assert output.shape == (3, 2, 4) - - -def test_net_ND(): - seed = 10 - shape = (3, 2, 1) - minval = np.array([[[1, 2]], [[3, 4]], [[5, 6]]]).astype(np.int32) - maxval = np.array([10]).astype(np.int32) - net = Net(shape, seed) - tminval, tmaxval = Tensor(minval), Tensor(maxval) - output = net(tminval, tmaxval) - print(output.asnumpy()) - assert output.shape == (3, 2, 2) diff --git a/tests/st/ops/ascend/test_aicpu_ops/test_uniform_real.py b/tests/st/ops/ascend/test_aicpu_ops/test_uniform_real.py index d5e643b3f9..7ab0b42e11 100644 --- a/tests/st/ops/ascend/test_aicpu_ops/test_uniform_real.py +++ b/tests/st/ops/ascend/test_aicpu_ops/test_uniform_real.py @@ -36,15 +36,3 @@ def test_net(): net = Net(shape, seed=seed) output = net() assert output.shape == (3, 2, 4) - - -def test_net_ND(): - seed = 10 - shape = (3, 2, 1) - a = np.array([[[1, 2]], [[3, 4]], [[5, 6]]]).astype(np.float32) - b = np.array([10]).astype(np.float32) - net = Net(shape, seed) - ta, tb = Tensor(a), Tensor(b) - output = net(ta, tb) - print(output.asnumpy()) - assert output.shape == (3, 2, 2) diff --git a/tests/st/ops/gpu/test_standard_normal.py b/tests/st/ops/gpu/test_standard_normal.py index efa4a99d74..deb1d0c1a7 100644 --- a/tests/st/ops/gpu/test_standard_normal.py +++ b/tests/st/ops/gpu/test_standard_normal.py @@ -13,6 +13,7 @@ # limitations under the License. # ============================================================================ +import pytest import mindspore.context as context import mindspore.nn as nn from mindspore.ops import operations as P @@ -31,7 +32,9 @@ class Net(nn.Cell): def construct(self): return self.stdnormal(self.shape) - +@pytest.mark.level0 +@pytest.mark.platform_x86_gpu_training +@pytest.mark.env_onecard def test_net(): seed = 10 seed2 = 10 diff --git a/tests/st/ops/gpu/test_uniform_int.py b/tests/st/ops/gpu/test_uniform_int.py new file mode 100644 index 0000000000..c4ce3a138c --- /dev/null +++ b/tests/st/ops/gpu/test_uniform_int.py @@ -0,0 +1,46 @@ +# Copyright 2020 Huawei Technologies Co., Ltd +# +# 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 pytest +import mindspore.context as context +import mindspore.nn as nn +from mindspore import Tensor +from mindspore.ops import operations as P +from mindspore.common import dtype as mstype + +context.set_context(mode=context.GRAPH_MODE, device_target="GPU") + + +class Net(nn.Cell): + def __init__(self, shape, seed=0, seed2=0): + super(Net, self).__init__() + self.uniformint = P.UniformInt(seed=seed) + self.shape = shape + + def construct(self, a, b): + return self.uniformint(self.shape, a, b) + +@pytest.mark.level0 +@pytest.mark.platform_x86_gpu_training +@pytest.mark.env_onecard +def test_net_1D(): + seed = 10 + shape = (3, 2, 4) + a = 1 + b = 5 + net = Net(shape, seed=seed) + ta, tb = Tensor(a, mstype.int32), Tensor(b, mstype.int32) + output = net(ta, tb) + assert output.shape == (3, 2, 4) diff --git a/tests/st/ops/gpu/test_uniform_real.py b/tests/st/ops/gpu/test_uniform_real.py index 2d9a6e035e..56fe932524 100644 --- a/tests/st/ops/gpu/test_uniform_real.py +++ b/tests/st/ops/gpu/test_uniform_real.py @@ -12,32 +12,30 @@ # See the License for the specific language governing permissions and # limitations under the License. # ============================================================================ + +import pytest import mindspore.context as context import mindspore.nn as nn -from mindspore import Tensor from mindspore.ops import operations as P -from mindspore.common import dtype as mstype context.set_context(mode=context.GRAPH_MODE, device_target="GPU") class Net(nn.Cell): - def __init__(self, shape, seed=0): + def __init__(self, shape, seed=0, seed2=0): super(Net, self).__init__() self.uniformreal = P.UniformReal(seed=seed) self.shape = shape - def construct(self, minval, maxval): - return self.uniformreal(self.shape, minval, maxval) - + def construct(self): + return self.uniformreal(self.shape) -def test_net_1D(): +@pytest.mark.level0 +@pytest.mark.platform_x86_gpu_training +@pytest.mark.env_onecard +def test_net(): seed = 10 shape = (3, 2, 4) - minval = 0.0 - maxval = 1.0 - net = Net(shape, seed) - tminval, tmaxval = Tensor(minval, mstype.float32), Tensor(maxval, mstype.float32) - output = net(tminval, tmaxval) - print(output.asnumpy()) + net = Net(shape, seed=seed) + output = net() assert output.shape == (3, 2, 4)