mindspore/tests/st/ops/cpu/test_random_gamma_op.py

65 lines
2.1 KiB
Python

# Copyright 2022 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 numpy as np
import mindspore as ms
import mindspore.nn as nn
from mindspore.ops import composite as C
from mindspore import Tensor
class RandomGammaTEST(nn.Cell):
def __init__(self, seed=0):
super(RandomGammaTEST, self).__init__()
self.seed = seed
def construct(self, shape, alpha, beta):
return C.gamma(shape, alpha, beta, self.seed)
@pytest.mark.level0
@pytest.mark.env_onecard
@pytest.mark.platform_x86_cpu
@pytest.mark.parametrize("dtype", [np.float64, np.float32, np.float16])
def test_gamma_op(dtype):
"""
Feature: Gamma cpu kernel
Description: test the gamma beta is a tensor.
Expectation: match to tensorflow benchmark.
"""
shape = (3, 1, 2)
alpha = Tensor(np.array([[3, 4], [5, 6]]), ms.float32)
beta = Tensor(np.array([3.0, 2.0]), ms.float32)
gamma_test = RandomGammaTEST(seed=3)
expect = np.array([3, 1, 2, 2, 2])
ms.set_context(mode=ms.GRAPH_MODE, device_target='CPU')
output = gamma_test(shape, alpha, beta)
assert (output.shape == expect).all()
ms.set_context(mode=ms.PYNATIVE_MODE)
output = ms.ops.gamma(shape, alpha, beta)
assert (output.shape == expect).all()
ms.set_context(mode=ms.GRAPH_MODE, device_target='CPU')
output = gamma_test(shape, alpha, None)
assert (output.shape == expect).all()
ms.set_context(mode=ms.PYNATIVE_MODE)
output = ms.ops.gamma(shape, alpha, None)
assert (output.shape == expect).all()