def test_version(self):
with patch('sys.stdout', new=StringIO()) as fake_out:
hyperdash_cli.version()
expected_output = ["hyperdash {}".format(get_hyperdash_version())]
for expected in expected_output:
assert_in(expected, fake_out.getvalue())
def test_monitor(self):
job_name = "some:job(name)with unsafe for files ystem chars"
logs = [
"Beginning machine learning...",
"Still training...",
"Done!",
# Handle unicode
"字",
# Huge log
"".join(
random.choice(lowercase_letters)
for x in range(10 * MAX_LOG_SIZE_BYTES)),
]
test_obj = {"some_obj_key": "some_value"}
expected_return = "final_result"
with patch("sys.stdout", new=StringIO()) as fake_out:
@monitor(job_name)
def test_job():
for log in logs:
print(log)
time.sleep(0.1)
print(test_obj)
time.sleep(0.1)
return expected_return
return_val = test_job()
assert return_val == expected_return
captured_out = fake_out.getvalue()
for log in logs:
if PY2:
assert log in captured_out.encode("utf-8")
continue
assert log in captured_out
assert str(test_obj) in captured_out
assert "error" not in captured_out
# Make sure logs were persisted
log_dir = get_hyperdash_logs_home_path_for_job(job_name)
latest_log_file = max([
os.path.join(log_dir, filename) for filename in os.listdir(log_dir)
],
key=os.path.getmtime)
with open(latest_log_file, "r") as log_file:
data = log_file.read()
for log in logs:
assert_in(log, data)
os.remove(latest_log_file)
# Make sure correct API name / version headers are sent
assert server_sdk_headers[0][API_KEY_NAME] == API_NAME_MONITOR
assert server_sdk_headers[0][
VERSION_KEY_NAME] == get_hyperdash_version()
def test_pipe(self):
job_name = "some_job_name"
inputs = [
"hello world",
"foo bar baz",
"this is the test script",
"字",
"{'some_obj_key': 'some_value'}",
]
r_d, w_d = os.pipe()
r_pipe = os.fdopen(r_d)
w_pipe = os.fdopen(w_d, 'w')
with patch('hyperdash_cli.cli.get_access_token_from_file',
Mock(return_value=DEFAULT_ACCESS_TOKEN)), patch(
'sys.stdin',
new=r_pipe), patch('sys.stdout',
new=StringIO()) as fake_out:
def writer():
for input_str in inputs:
w_pipe.write(input_str)
w_pipe.flush()
w_pipe.close()
writer_thread = Thread(target=writer)
writer_thread.start()
hyperdash_cli.pipe(argparse.Namespace(name=job_name))
for expected in inputs:
if PY2:
assert_in(expected, fake_out.getvalue().encode("utf-8"))
continue
assert_in(expected, fake_out.getvalue())
# Make sure correct API name / version headers are sent
assert server_sdk_headers[0][API_KEY_NAME] == API_NAME_CLI_PIPE
assert server_sdk_headers[0][
VERSION_KEY_NAME] == get_hyperdash_version()
# Make sure logs were persisted
log_dir = get_hyperdash_logs_home_path_for_job(job_name)
latest_log_file = max([
os.path.join(log_dir, filename) for filename in os.listdir(log_dir)
],
key=os.path.getmtime)
with open(latest_log_file, 'r') as log_file:
data = log_file.read()
for expected in inputs:
assert_in(expected, data)
os.remove(latest_log_file)
def test_monitor_cell(self):
expected_logs = [
"Beginning machine learning...",
"Still training...",
"Done!",
# Handle unicode
"хнЧ"
]
with open("./tests/jupyter_test_file.py.ipynb") as f:
nb = nbformat.read(f, as_version=4.0)
ep = ExecutePreprocessor(timeout=5000, kernel_name="python")
result = ep.preprocess(nb, {})
# Accumulate all output from cell 2
all_stdout = ""
second_cell_output = result[0]["cells"][1]["outputs"]
for output in second_cell_output:
if output.name == "stdout":
all_stdout = all_stdout + output.text
# Assert on all output from cell2
for log in expected_logs:
if PY2:
assert_in(log, all_stdout.encode("utf-8"))
continue
assert_in(log, all_stdout)
# Verify that variables declared in previous cells can be affected
third_cell_output = result[0]["cells"][2]["outputs"]
assert third_cell_output[0].text == "a=1\n"
# Make sure correct API name / version headers are sent
assert server_sdk_headers[0][API_KEY_NAME] == API_NAME_JUPYTER
assert server_sdk_headers[0][
VERSION_KEY_NAME] == get_hyperdash_version()
# Make sure logs were persisted
log_dir = get_hyperdash_logs_home_path_for_job("test_jupyter")
latest_log_file = max([
os.path.join(log_dir, filename) for filename in os.listdir(log_dir)
],
key=os.path.getmtime)
with open(latest_log_file, 'r') as log_file:
data = log_file.read()
for log in expected_logs:
assert_in(log, data)
os.remove(latest_log_file)
def test_run(self):
job_name = "some_job_name"
with patch('hyperdash_cli.cli.get_access_token_from_file',
Mock(return_value=DEFAULT_ACCESS_TOKEN)), patch(
'sys.stdout', new=StringIO()) as fake_out:
hyperdash_cli.run(
argparse.Namespace(name=job_name,
args=[
"echo",
"hello world",
"&&",
"echo",
"foo bar baz",
"&&",
"python",
"tests/test_script_for_run_test.py",
]))
expected_output = [
"hello world",
"foo bar baz",
"this is the test script",
"字",
"{'some_obj_key': 'some_value'}",
]
for expected in expected_output:
if PY2:
assert_in(expected, fake_out.getvalue().encode("utf-8"))
continue
assert_in(expected, fake_out.getvalue())
# Make sure correct API name / version headers are sent
assert server_sdk_headers[0][API_KEY_NAME] == API_NAME_CLI_RUN
assert server_sdk_headers[0][
VERSION_KEY_NAME] == get_hyperdash_version()
# Make sure logs were persisted
log_dir = get_hyperdash_logs_home_path_for_job(job_name)
latest_log_file = max([
os.path.join(log_dir, filename) for filename in os.listdir(log_dir)
],
key=os.path.getmtime)
with open(latest_log_file, 'r') as log_file:
data = log_file.read()
for expected in expected_output:
assert_in(expected, data)
os.remove(latest_log_file)
def version(args=None):
print("hyperdash {}".format(get_hyperdash_version()))
def test_experiment(self):
# Run a test job via the Experiment API
# Make sure log file is where is supposed to be
# look at decorator
# verify run start/stop is sent
with patch("sys.stdout", new=StringIO()) as faked_out:
exp = Experiment("MNIST")
exp.log("test print")
exp.param("batch size", 32)
for i in exp.iter(2):
time.sleep(1)
exp.metric("accuracy", i * 0.2)
time.sleep(0.1)
exp.end()
# Test params match what is expected
params_messages = []
for msg in server_sdk_messages:
payload = msg["payload"]
if "params" in payload:
params_messages.append(payload)
expect_params = [
{
"params": {
"batch size": 32,
},
"is_internal": False,
},
{
"params": {
"hd_iter_0_epochs": 2,
},
"is_internal": True,
},
]
assert len(expect_params) == len(params_messages)
for i, message in enumerate(params_messages):
assert message == expect_params[i]
# Test metrics match what is expected
metrics_messages = []
for msg in server_sdk_messages:
payload = msg["payload"]
if "name" in payload:
metrics_messages.append(payload)
expect_metrics = [
{
"is_internal": True,
"name": "hd_iter_0",
"value": 0
},
{
"is_internal": False,
"name": "accuracy",
"value": 0
},
{
"is_internal": True,
"name": "hd_iter_0",
"value": 1
},
{
"is_internal": False,
"name": "accuracy",
"value": 0.2
},
]
assert len(expect_metrics) == len(metrics_messages)
for i, message in enumerate(metrics_messages):
assert message == expect_metrics[i]
captured_out = faked_out.getvalue()
assert "error" not in captured_out
# Make sure correct API name / version headers are sent
assert server_sdk_headers[0][API_KEY_NAME] == API_NAME_EXPERIMENT
assert server_sdk_headers[0][
VERSION_KEY_NAME] == get_hyperdash_version()
# Make sure logs were persisted
expect_logs = [
"{ batch size: 32 }",
"test print",
"| Iteration 0 of 1 |",
"| accuracy: 0.000000 |",
]
log_dir = get_hyperdash_logs_home_path_for_job("MNIST")
latest_log_file = max([
os.path.join(log_dir, filename) for filename in os.listdir(log_dir)
],
key=os.path.getmtime)
with open(latest_log_file, "r") as log_file:
data = log_file.read()
for log in expect_logs:
assert_in(log, data)
os.remove(latest_log_file)
def test_tensorboard(self):
job_name = "some_job_name"
with patch('hyperdash_cli.cli.get_access_token_from_file',
Mock(return_value=DEFAULT_ACCESS_TOKEN)), patch(
'sys.stdout', new=StringIO()) as fake_out:
hyperdash_cli.tensorboard(
argparse.Namespace(
name=job_name,
logdir="tests/test_tensorboard_logs",
backfill=True,
),
is_test=True,
)
# This is not all the datapoints in the tensorboard logs, but only these ones are included
# due to the default 1s sampling
expected_metrics = [{
u'timestamp': 1512945127487,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'job_name': u'some_job_name'
},
u'type': u'run_started'
}, {
u'timestamp': 1512945127489,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944548971,
u'is_internal': False,
u'name': u'loss',
u'value': 2.3025853633880615
},
u'type': u'metric'
}, {
u'timestamp': 1512945127492,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944549971,
u'is_internal': False,
u'name': u'loss',
u'value': 0.7624818682670593
},
u'type': u'metric'
}, {
u'timestamp': 1512945127495,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944550972,
u'is_internal': False,
u'name': u'loss',
u'value': 0.5105720162391663
},
u'type': u'metric'
}, {
u'timestamp': 1512945127497,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944551976,
u'is_internal': False,
u'name': u'loss',
u'value': 0.5286356210708618
},
u'type': u'metric'
}, {
u'timestamp': 1512945127500,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944553023,
u'is_internal': False,
u'name': u'loss',
u'value': 0.455232173204422
},
u'type': u'metric'
}, {
u'timestamp': 1512945127503,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944554024,
u'is_internal': False,
u'name': u'loss',
u'value': 0.372854620218277
},
u'type': u'metric'
}, {
u'timestamp': 1512945127505,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944555025,
u'is_internal': False,
u'name': u'loss',
u'value': 0.4262654483318329
},
u'type': u'metric'
}, {
u'timestamp': 1512945127508,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944556025,
u'is_internal': False,
u'name': u'loss',
u'value': 0.38998115062713623
},
u'type': u'metric'
}, {
u'timestamp': 1512945127510,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944557025,
u'is_internal': False,
u'name': u'loss',
u'value': 0.38911107182502747
},
u'type': u'metric'
}, {
u'timestamp': 1512945127512,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944558026,
u'is_internal': False,
u'name': u'loss',
u'value': 0.4348866641521454
},
u'type': u'metric'
}, {
u'timestamp': 1512945127516,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944559027,
u'is_internal': False,
u'name': u'loss',
u'value': 0.286268413066864
},
u'type': u'metric'
}, {
u'timestamp': 1512945127519,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944560028,
u'is_internal': False,
u'name': u'loss',
u'value': 0.3003489673137665
},
u'type': u'metric'
}, {
u'timestamp': 1512945127523,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944561029,
u'is_internal': False,
u'name': u'loss',
u'value': 0.3317962884902954
},
u'type': u'metric'
}, {
u'timestamp': 1512945127525,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944562034,
u'is_internal': False,
u'name': u'loss',
u'value': 0.27931177616119385
},
u'type': u'metric'
}, {
u'timestamp': 1512945127526,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944563042,
u'is_internal': False,
u'name': u'loss',
u'value': 0.6486308574676514
},
u'type': u'metric'
}, {
u'timestamp': 1512945127528,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944564109,
u'is_internal': False,
u'name': u'loss',
u'value': 0.5528809428215027
},
u'type': u'metric'
}, {
u'timestamp': 1512945127531,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944565113,
u'is_internal': False,
u'name': u'loss',
u'value': 0.3118564486503601
},
u'type': u'metric'
}, {
u'timestamp': 1512945127542,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944566113,
u'is_internal': False,
u'name': u'loss',
u'value': 0.48642101883888245
},
u'type': u'metric'
}, {
u'timestamp': 1512945127544,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944567114,
u'is_internal': False,
u'name': u'loss',
u'value': 0.2462320178747177
},
u'type': u'metric'
}, {
u'timestamp': 1512945127549,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944568117,
u'is_internal': False,
u'name': u'loss',
u'value': 0.2997052073478699
},
u'type': u'metric'
}, {
u'timestamp': 1512945127553,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944569119,
u'is_internal': False,
u'name': u'loss',
u'value': 0.19338417053222656
},
u'type': u'metric'
}, {
u'timestamp': 1512945127557,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944570120,
u'is_internal': False,
u'name': u'loss',
u'value': 0.4237367510795593
},
u'type': u'metric'
}, {
u'timestamp': 1512945127560,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944571121,
u'is_internal': False,
u'name': u'loss',
u'value': 0.2270836979150772
},
u'type': u'metric'
}, {
u'timestamp': 1512945127561,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944548971,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.14000000059604645
},
u'type': u'metric'
}, {
u'timestamp': 1512945127563,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944549971,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.800000011920929
},
u'type': u'metric'
}, {
u'timestamp': 1512945127566,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944550972,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8999999761581421
},
u'type': u'metric'
}, {
u'timestamp': 1512945127568,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944551976,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8600000143051147
},
u'type': u'metric'
}, {
u'timestamp': 1512945127570,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944553023,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9100000262260437
},
u'type': u'metric'
}, {
u'timestamp': 1512945127573,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944554024,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8999999761581421
},
u'type': u'metric'
}, {
u'timestamp': 1512945127575,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944555025,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8899999856948853
},
u'type': u'metric'
}, {
u'timestamp': 1512945127578,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944556025,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8799999952316284
},
u'type': u'metric'
}, {
u'timestamp': 1512945127580,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944557025,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8899999856948853
},
u'type': u'metric'
}, {
u'timestamp': 1512945127582,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944558026,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8799999952316284
},
u'type': u'metric'
}, {
u'timestamp': 1512945127585,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944559027,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9599999785423279
},
u'type': u'metric'
}, {
u'timestamp': 1512945127587,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944560028,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8999999761581421
},
u'type': u'metric'
}, {
u'timestamp': 1512945127591,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944561029,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9200000166893005
},
u'type': u'metric'
}, {
u'timestamp': 1512945127593,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944562034,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9300000071525574
},
u'type': u'metric'
}, {
u'timestamp': 1512945127594,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944563042,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8500000238418579
},
u'type': u'metric'
}, {
u'timestamp': 1512945127596,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944564109,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8199999928474426
},
u'type': u'metric'
}, {
u'timestamp': 1512945127599,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944565113,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9300000071525574
},
u'type': u'metric'
}, {
u'timestamp': 1512945127602,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944566113,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8600000143051147
},
u'type': u'metric'
}, {
u'timestamp': 1512945127603,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944567114,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.949999988079071
},
u'type': u'metric'
}, {
u'timestamp': 1512945127605,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944568117,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9300000071525574
},
u'type': u'metric'
}, {
u'timestamp': 1512945127608,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944569119,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9599999785423279
},
u'type': u'metric'
}, {
u'timestamp': 1512945127610,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944570120,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.8799999952316284
},
u'type': u'metric'
}, {
u'timestamp': 1512945127612,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'timestamp': 1512944571121,
u'is_internal': False,
u'name': u'accuracy',
u'value': 0.9300000071525574
},
u'type': u'metric'
}, {
u'timestamp': 1512945128493,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'body':
u'This run of some_job_name ran for 0:00:01 and logs are available locally at: /Users/richie/.hyperdash/logs/some-job-name/some-job-name_2017-12-10t17-32-07-487283.log\n',
u'uuid': u'2a00ed85-d9a0-4df5-ab2d-fee35fb1dd00',
u'level': u'INFO'
},
u'type': u'log'
}, {
u'timestamp': 1512945128493,
u'sdk_run_uuid': u'77972e75-6266-4d2a-94b7-25117b7dcd08',
u'payload': {
u'final_status': u'success'
},
u'type': u'run_ended'
}]
# TODO: Make this part pass in PY3 (for some reason the sampling is slightly different in PY3)
if PY2:
for i, message in enumerate(server_sdk_messages):
if message['type'] == 'metric':
assert message['payload'] == expected_metrics[i]['payload']
else:
assert len(expected_metrics) > 20
# Make sure correct API name / version headers are sent
assert server_sdk_headers[0][API_KEY_NAME] == API_NAME_CLI_TENSORBOARD
assert server_sdk_headers[0][
VERSION_KEY_NAME] == get_hyperdash_version()