forked from mindspore-Ecosystem/mindspore
82 lines
2.8 KiB
Python
82 lines
2.8 KiB
Python
# Copyright 2019 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.
|
|
# ============================================================================
|
|
"""Summary cpu st."""
|
|
import os
|
|
import platform
|
|
import tempfile
|
|
|
|
import numpy as np
|
|
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.train.summary.summary_record import SummaryRecord
|
|
from tests.summary_utils import SummaryReader
|
|
|
|
context.set_context(mode=context.GRAPH_MODE, device_target='CPU')
|
|
|
|
|
|
class SummaryNet(nn.Cell):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self.scalar_summary = P.ScalarSummary()
|
|
self.image_summary = P.ImageSummary()
|
|
self.tensor_summary = P.TensorSummary()
|
|
self.histogram_summary = P.HistogramSummary()
|
|
|
|
def construct(self, image_tensor):
|
|
self.image_summary("image", image_tensor)
|
|
self.tensor_summary("tensor", image_tensor)
|
|
self.histogram_summary("histogram", image_tensor)
|
|
scalar = image_tensor[0][0][0][0]
|
|
self.scalar_summary("scalar", scalar)
|
|
return scalar
|
|
|
|
|
|
def train_summary_record(test_writer, steps):
|
|
"""Train and record summary."""
|
|
net = SummaryNet()
|
|
out_me_dict = {}
|
|
for i in range(0, steps):
|
|
image_tensor = Tensor(np.array([[[[i]]]]).astype(np.float32))
|
|
out_put = net(image_tensor)
|
|
test_writer.record(i)
|
|
out_me_dict[i] = out_put.asnumpy()
|
|
return out_me_dict
|
|
|
|
|
|
@pytest.mark.level0
|
|
@pytest.mark.platform_x86_cpu
|
|
@pytest.mark.env_onecard
|
|
def test_summary_step2_summary_record1():
|
|
"""Test record 10 step summary."""
|
|
if platform.system() == "Windows":
|
|
# Summary does not support windows currently.
|
|
return
|
|
|
|
with tempfile.TemporaryDirectory() as tmp_dir:
|
|
steps = 2
|
|
with SummaryRecord(tmp_dir) as test_writer:
|
|
train_summary_record(test_writer, steps=steps)
|
|
|
|
file_name = os.path.realpath(test_writer.full_file_name)
|
|
with SummaryReader(file_name) as summary_writer:
|
|
for _ in range(steps):
|
|
event = summary_writer.read_event()
|
|
tags = set(value.tag for value in event.summary.value)
|
|
assert tags == {'tensor', 'histogram', 'scalar', 'image'}
|