def test_histogram_summary_nan_inf():
"""Test histogram summary, input tensor has nan."""
with tempfile.TemporaryDirectory() as tmp_dir:
with SummaryRecord(tmp_dir,
file_suffix="_MS_HISTOGRAM") as test_writer:
dim1 = 100
dim2 = 100
arr = np.ones([dim1, dim2])
arr[0][0] = np.nan
arr[0][1] = np.inf
arr[0][2] = -np.inf
test_data = _wrap_test_data(Tensor(arr))
_cache_summary_tensor_data(test_data)
test_writer.record(step=1)
file_name = os.path.join(tmp_dir, test_writer.event_file_name)
reader = SummaryReader(file_name)
event = reader.read_event()
LOG.debug(event)
assert event.summary.value[0].histogram.nan_count == 1
def summary_cb_for_save_op(summary_list):
"""
The summary callback function for MindSpore.
Will be executed by summary op.
Args:
summary_list (list): Format is like [{"name": tag_name, "data": tensor},...] and value is Scalar/Tensor.
Returns:
bool, true: means save summary success.
"""
ret = _cache_summary_tensor_data(summary_list)
return ret
def test_histogram_multi_summary():
"""Test histogram multiple step."""
with tempfile.TemporaryDirectory() as tmp_dir:
test_writer = SummaryRecord(tmp_dir, file_suffix="_MS_HISTOGRAM")
rng = np.random.RandomState(10)
size = 50
num_step = 5
for i in range(num_step):
arr = rng.normal(size=size)
test_data = _wrap_test_data(Tensor(arr))
_cache_summary_tensor_data(test_data)
test_writer.record(step=i)
test_writer.close()
file_name = os.path.join(tmp_dir, test_writer.event_file_name)
reader = SummaryReader(file_name)
for _ in range(num_step):
event = reader.read_event()
assert event.summary.value[0].histogram.count == size
def test_image_summary_data():
""" test_image_summary_data """
dataset = get_dataset()
test_data_list = []
i = 1
for next_element in dataset:
tag = "image_" + str(i) + "[:Image]"
dct = {}
dct["name"] = tag
dct["data"] = Tensor(next_element[0])
test_data_list.append(dct)
i += 1
log.debug("begin test_image_summary_sample")
# step 0: create the thread
with SummaryRecord(SUMMARY_DIR, file_suffix="_MS_IMAGE") as test_writer:
# step 1: create the test data for summary
# step 2: create the Event
_cache_summary_tensor_data(test_data_list)
test_writer.record(1)
log.debug("finished test_image_summary_sample")
