def test_update_rest_grpc(self, resnet_multiple_batch_sizes, get_test_dir,
start_server_update_flow_specific,
create_grpc_channel):
resnet, resnet_bs4, resnet_bs8 = resnet_multiple_batch_sizes
dir = get_test_dir + '/saved_models/' + 'update/'
# ensure model dir is empty at the beginning
shutil.rmtree(dir, ignore_errors=True)
stub = create_grpc_channel('localhost:9008', PREDICTION_SERVICE)
resnet_copy_dir = copy_model(resnet, 1, dir)
resnet_bs4_copy_dir = copy_model(resnet_bs4, 4, dir)
time.sleep(8)
# Available versions: 1, 4
print("Getting info about resnet model")
model_name = 'resnet'
in_name = 'map/TensorArrayStack/TensorArrayGatherV3'
out_name = 'softmax_tensor'
expected_input_metadata_v1 = {
in_name: {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name: {
'dtype': 1,
'shape': [1, 1001]
}
}
request = get_model_metadata(model_name=model_name, version=1)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_latest = get_model_metadata_response_rest(rest_url)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
request_v4 = get_model_metadata(model_name=model_name, version=4)
response_v4 = stub.GetModelMetadata(request_v4, 10)
print("response", response_v4)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_latest)
assert response_v4.model_spec.name == response_latest.model_spec.name
assert input_metadata_v4 == input_metadata_latest
assert output_metadata_v4 == output_metadata_latest
shutil.rmtree(resnet_bs4_copy_dir)
resnet_bs8_copy_dir = copy_model(resnet_bs8, 3, dir)
time.sleep(3)
# Available versions: 1, 3
request_latest = get_model_metadata(model_name=model_name)
response_latest = stub.GetModelMetadata(request_latest, 10)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
rest_url = 'http://localhost:5563/v1/models/resnet/versions/3/metadata'
response_v3 = get_model_metadata_response_rest(rest_url)
print("response", response_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert response_v3.model_spec.name == response_latest.model_spec.name
assert input_metadata_v3 == input_metadata_latest
assert output_metadata_v3 == output_metadata_latest
# Available versions: 1, 3, 4
time.sleep(3)
resnet_bs4_copy_dir = copy_model(resnet_bs4, 4, dir)
time.sleep(3)
rest_url = 'http://localhost:5563/v1/models/resnet/versions/1/metadata'
response_v1 = get_model_metadata_response_rest(rest_url)
input_metadata_v1, output_metadata_v1 = model_metadata_response(
response=response_v1)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata_v1
assert expected_output_metadata_v1 == output_metadata_v1
expected_input_metadata_v3 = {
in_name: {
'dtype': 1,
'shape': [8, 3, 224, 224]
}
}
expected_output_metadata_v3 = {
out_name: {
'dtype': 1,
'shape': [8, 1001]
}
}
request_v3 = get_model_metadata(model_name=model_name, version=3)
response_v3 = stub.GetModelMetadata(request_v3, 10)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert model_name == response.model_spec.name
assert expected_input_metadata_v3 == input_metadata_v3
assert expected_output_metadata_v3 == output_metadata_v3
expected_input_metadata_v4 = {
in_name: {
'dtype': 1,
'shape': [4, 3, 224, 224]
}
}
expected_output_metadata_v4 = {
out_name: {
'dtype': 1,
'shape': [4, 1001]
}
}
rest_url = 'http://localhost:5563/v1/models/resnet/versions/4/metadata'
response_v4 = get_model_metadata_response_rest(rest_url)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_v4)
assert model_name == response_v4.model_spec.name
assert expected_input_metadata_v4 == input_metadata_v4
assert expected_output_metadata_v4 == output_metadata_v4
shutil.rmtree(resnet_copy_dir)
shutil.rmtree(resnet_bs4_copy_dir)
shutil.rmtree(resnet_bs8_copy_dir)
def test_specific_version_rest(self, resnet_multiple_batch_sizes,
get_test_dir,
start_server_update_flow_specific):
resnet, resnet_bs4, resnet_bs8 = resnet_multiple_batch_sizes
dir = get_test_dir + '/saved_models/' + 'update/'
# ensure model dir is empty at the beginning
shutil.rmtree(dir, ignore_errors=True)
resnet_copy_dir = copy_model(resnet, 1, dir)
resnet_bs4_copy_dir = copy_model(resnet_bs4, 4, dir)
time.sleep(8)
in_name = 'map/TensorArrayStack/TensorArrayGatherV3'
out_name = 'softmax_tensor'
# Available versions: 1, 4
print("Getting info about resnet model")
model_name = 'resnet'
expected_input_metadata_v1 = {
in_name: {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name: {
'dtype': 1,
'shape': [1, 1001]
}
}
rest_url_latest = 'http://localhost:5563/v1/models/resnet/' \
'versions/1/metadata'
response = get_model_metadata_response_rest(rest_url_latest)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_latest = get_model_metadata_response_rest(rest_url)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
rest_url_v4 = 'http://localhost:5563/v1/models/resnet/' \
'versions/4/metadata'
response_v4 = get_model_metadata_response_rest(rest_url_v4)
print("response", response_v4)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_latest)
assert response_v4.model_spec.name == response_latest.model_spec.name
assert input_metadata_v4 == input_metadata_latest
assert output_metadata_v4 == output_metadata_latest
# Model status check
rest_status_url = 'http://localhost:5563/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_bs4_copy_dir)
resnet_bs8_copy_dir = copy_model(resnet_bs8, 3, dir)
time.sleep(10)
# Available versions: 1, 3
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_latest = get_model_metadata_response_rest(rest_url)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
rest_url_v3 = 'http://localhost:5563/v1/models/resnet/' \
'versions/3/metadata'
response_v3 = get_model_metadata_response_rest(rest_url_v3)
print("response", response_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert response_v3.model_spec.name == response_latest.model_spec.name
assert input_metadata_v3 == input_metadata_latest
assert output_metadata_v3 == output_metadata_latest
# Model status check
rest_status_url = 'http://localhost:5563/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
if version_status.version == 4:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 1 or version_status.version == 3:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
# Available versions: 1, 3, 4
resnet_bs4_copy_dir = copy_model(resnet_bs4, 4, dir)
time.sleep(10)
rest_url_v1 = 'http://localhost:5563/v1/models/resnet/' \
'versions/1/metadata'
response_v1 = get_model_metadata_response_rest(rest_url_v1)
input_metadata_v1, output_metadata_v1 = model_metadata_response(
response=response_v1)
assert model_name == response_v1.model_spec.name
assert expected_input_metadata_v1 == input_metadata_v1
assert expected_output_metadata_v1 == output_metadata_v1
expected_input_metadata_v3 = {
in_name: {
'dtype': 1,
'shape': [8, 3, 224, 224]
}
}
expected_output_metadata_v3 = {
out_name: {
'dtype': 1,
'shape': [8, 1001]
}
}
rest_url_v3 = 'http://localhost:5563/v1/models/resnet/' \
'versions/3/metadata'
response_v3 = get_model_metadata_response_rest(rest_url_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert model_name == response_v3.model_spec.name
assert expected_input_metadata_v3 == input_metadata_v3
assert expected_output_metadata_v3 == output_metadata_v3
expected_input_metadata_v4 = {
in_name: {
'dtype': 1,
'shape': [4, 3, 224, 224]
}
}
expected_output_metadata_v4 = {
out_name: {
'dtype': 1,
'shape': [4, 1001]
}
}
response_v4 = get_model_metadata_response_rest(rest_url)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_v4)
assert model_name == response_v4.model_spec.name
assert expected_input_metadata_v4 == input_metadata_v4
assert expected_output_metadata_v4 == output_metadata_v4
# Model status check
rest_status_url = 'http://localhost:5563/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_copy_dir)
shutil.rmtree(resnet_bs4_copy_dir)
shutil.rmtree(resnet_bs8_copy_dir)
time.sleep(10)
def test_latest_version_rest(self, resnet_multiple_batch_sizes,
get_test_dir,
start_server_update_flow_latest):
resnet, resnet_bs4, resnet_bs8 = resnet_multiple_batch_sizes
dir = get_test_dir + '/saved_models/' + 'update/'
# ensure model dir is empty at the beginning
shutil.rmtree(dir, ignore_errors=True)
resnet_copy_dir = copy_model(resnet, 1, dir)
time.sleep(8)
print("Getting info about resnet model")
model_name = 'resnet'
in_name = 'map/TensorArrayStack/TensorArrayGatherV3'
out_name = 'softmax_tensor'
expected_input_metadata_v1 = {
in_name: {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name: {
'dtype': 1,
'shape': [1, 1001]
}
}
rest_url = 'http://localhost:5562/v1/models/resnet/metadata'
response = get_model_metadata_response_rest(rest_url)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
# Model status check before update
rest_status_url = 'http://localhost:5562/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
version_status = versions_statuses[0]
assert len(versions_statuses) == 1
assert version_status.version == 1
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_copy_dir)
resnet_bs4_copy_dir = copy_model(resnet_bs4, 2, dir)
time.sleep(10)
expected_input_metadata = {
in_name: {
'dtype': 1,
'shape': [4, 3, 224, 224]
}
}
expected_output_metadata = {out_name: {'dtype': 1, 'shape': [4, 1001]}}
response = get_model_metadata_response_rest(rest_url)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata == input_metadata
assert expected_output_metadata == output_metadata
# Model status check after update
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 2]
if version_status.version == 1:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 2:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_bs4_copy_dir)
time.sleep(10)
def test_latest_version(self, resnet_multiple_batch_sizes, get_test_dir,
start_server_update_flow_latest,
create_grpc_channel):
resnet, resnet_bs4, resnet_bs8 = resnet_multiple_batch_sizes
dir = get_test_dir + '/saved_models/' + 'update/'
# ensure model dir is empty at the beginning
shutil.rmtree(dir, ignore_errors=True)
resnet_v1_copy_dir = copy_model(resnet, 1, dir)
time.sleep(8)
stub = create_grpc_channel('localhost:9007', PREDICTION_SERVICE)
status_stub = create_grpc_channel('localhost:9007', MODEL_SERVICE)
print("Getting info about resnet model")
model_name = 'resnet'
in_name = 'map/TensorArrayStack/TensorArrayGatherV3'
out_name = 'softmax_tensor'
expected_input_metadata_v1 = {
in_name: {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name: {
'dtype': 1,
'shape': [1, 1001]
}
}
request = get_model_metadata(model_name=model_name)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
# Model status check before update
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
version_status = versions_statuses[0]
assert len(versions_statuses) == 1
assert version_status.version == 1
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
resnet_v2_copy_dir = copy_model(resnet_bs4, 2, dir)
time.sleep(10)
expected_input_metadata_v2 = {
in_name: {
'dtype': 1,
'shape': [4, 3, 224, 224]
}
}
expected_output_metadata_v2 = {
out_name: {
'dtype': 1,
'shape': [4, 1001]
}
}
request = get_model_metadata(model_name=model_name)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v2 == input_metadata
assert expected_output_metadata_v2 == output_metadata
# Model status check after update
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 2]
if version_status.version == 1:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 2:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v1_copy_dir)
shutil.rmtree(resnet_v2_copy_dir)
time.sleep(10)
def test_specific_version(self, resnet_multiple_batch_sizes, get_test_dir,
start_server_update_flow_specific,
create_grpc_channel):
resnet, resnet_bs4, resnet_bs8 = resnet_multiple_batch_sizes
dir = get_test_dir + '/saved_models/' + 'update/'
# ensure model dir is empty at the beginning
shutil.rmtree(dir, ignore_errors=True)
stub = create_grpc_channel('localhost:9008', PREDICTION_SERVICE)
status_stub = create_grpc_channel('localhost:9008', MODEL_SERVICE)
resnet_copy_dir = copy_model(resnet, 1, dir)
resnet_bs4_copy_dir = copy_model(resnet_bs4, 4, dir)
# This could be replaced with status polling
time.sleep(8)
# Available versions: 1, 4
print("Getting info about resnet model")
model_name = 'resnet'
in_name = 'map/TensorArrayStack/TensorArrayGatherV3'
out_name = 'softmax_tensor'
expected_input_metadata_v1 = {
in_name: {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name: {
'dtype': 1,
'shape': [1, 1001]
}
}
request = get_model_metadata(model_name=model_name, version=1)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
request_latest = get_model_metadata(model_name=model_name)
response_latest = stub.GetModelMetadata(request_latest, 10)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
request_v4 = get_model_metadata(model_name=model_name, version=4)
response_v4 = stub.GetModelMetadata(request_v4, 10)
print("response", response_v4)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_latest)
assert response_v4.model_spec.name == response_latest.model_spec.name
assert input_metadata_v4 == input_metadata_latest
assert output_metadata_v4 == output_metadata_latest
# Model status check
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_bs4_copy_dir)
resnet_bs8_copy_dir = copy_model(resnet_bs8, 3, dir)
time.sleep(10)
# Available versions: 1, 3
request_latest = get_model_metadata(model_name=model_name)
response_latest = stub.GetModelMetadata(request_latest, 10)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
request_v3 = get_model_metadata(model_name=model_name, version=3)
response_v3 = stub.GetModelMetadata(request_v3, 10)
print("response", response_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert response_v3.model_spec.name == response_latest.model_spec.name
assert input_metadata_v3 == input_metadata_latest
assert output_metadata_v3 == output_metadata_latest
# Model status check
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
if version_status.version == 4:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 1 or version_status.version == 3:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
# Available versions: 1, 3, 4
resnet_bs4_copy_dir = copy_model(resnet_bs4, 4, dir)
time.sleep(10)
request_v1 = get_model_metadata(model_name=model_name, version=1)
response_v1 = stub.GetModelMetadata(request_v1, 10)
input_metadata_v1, output_metadata_v1 = model_metadata_response(
response=response_v1)
assert model_name == response_v1.model_spec.name
assert expected_input_metadata_v1 == input_metadata_v1
assert expected_output_metadata_v1 == output_metadata_v1
expected_input_metadata_v3 = {
in_name: {
'dtype': 1,
'shape': [8, 3, 224, 224]
}
}
expected_output_metadata_v3 = {
out_name: {
'dtype': 1,
'shape': [8, 1001]
}
}
request_v3 = get_model_metadata(model_name=model_name, version=3)
response_v3 = stub.GetModelMetadata(request_v3, 10)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert model_name == response_v3.model_spec.name
assert expected_input_metadata_v3 == input_metadata_v3
assert expected_output_metadata_v3 == output_metadata_v3
expected_input_metadata_v4 = {
in_name: {
'dtype': 1,
'shape': [4, 3, 224, 224]
}
}
expected_output_metadata_v4 = {
out_name: {
'dtype': 1,
'shape': [4, 1001]
}
}
request_v4 = get_model_metadata(model_name=model_name)
response_v4 = stub.GetModelMetadata(request_v4, 10)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_v4)
assert model_name == response_v4.model_spec.name
assert expected_input_metadata_v4 == input_metadata_v4
assert expected_output_metadata_v4 == output_metadata_v4
# Model status check
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_copy_dir)
shutil.rmtree(resnet_bs4_copy_dir)
shutil.rmtree(resnet_bs8_copy_dir)
time.sleep(10)
def test_update_rest_grpc(self, download_two_model_versions,
resnet_2_out_model_downloader, get_test_dir,
start_server_update_flow_specific,
create_grpc_channel):
resnet_v1, resnet_v2 = download_two_model_versions
resnet_2_out = resnet_2_out_model_downloader
dir = get_test_dir + '/saved_models/' + 'update/'
stub = create_grpc_channel('localhost:9008', PREDICTION_SERVICE)
resnet_v1_copy_dir = copy_model(resnet_v1, 1, dir)
resnet_2_out_copy_dir = copy_model(resnet_2_out, 4, dir)
time.sleep(8)
# Available versions: 1, 4
print("Getting info about resnet model")
model_name = 'resnet'
out_name_v1 = 'resnet_v1_50/predictions/Reshape_1'
expected_input_metadata_v1 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name_v1: {
'dtype': 1,
'shape': [1, 1000]
}
}
request = get_model_metadata(model_name=model_name, version=1)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_latest = get_model_metadata_response_rest(rest_url)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
request_v4 = get_model_metadata(model_name=model_name, version=4)
response_v4 = stub.GetModelMetadata(request_v4, 10)
print("response", response_v4)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_latest)
assert response_v4.model_spec.name == response_latest.model_spec.name
assert input_metadata_v4 == input_metadata_latest
assert output_metadata_v4 == output_metadata_latest
shutil.rmtree(resnet_2_out_copy_dir)
resnet_v2_copy_dir = copy_model(resnet_v2, 3, dir)
time.sleep(3)
# Available versions: 1, 3
request_latest = get_model_metadata(model_name=model_name)
response_latest = stub.GetModelMetadata(request_latest, 10)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
rest_url = 'http://localhost:5563/v1/models/resnet/versions/3/metadata'
response_v3 = get_model_metadata_response_rest(rest_url)
print("response", response_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert response_v3.model_spec.name == response_latest.model_spec.name
assert input_metadata_v3 == input_metadata_latest
assert output_metadata_v3 == output_metadata_latest
# Available versions: 1, 3, 4
resnet_2_out_copy_dir = copy_model(resnet_2_out, 4, dir)
time.sleep(3)
rest_url = 'http://localhost:5563/v1/models/resnet/versions/1/metadata'
response_v1 = get_model_metadata_response_rest(rest_url)
input_metadata_v1, output_metadata_v1 = model_metadata_response(
response=response_v1)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata_v1
assert expected_output_metadata_v1 == output_metadata_v1
out_name_v3 = 'resnet_v2_50/predictions/Reshape_1'
expected_input_metadata_v3 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v3 = {
out_name_v3: {
'dtype': 1,
'shape': [1, 1001]
}
}
request_v3 = get_model_metadata(model_name=model_name, version=3)
response_v3 = stub.GetModelMetadata(request_v3, 10)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert model_name == response.model_spec.name
assert expected_input_metadata_v3 == input_metadata_v3
assert expected_output_metadata_v3 == output_metadata_v3
expected_input_metadata_v4 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v4 = {
'res5c_branch2c1': {
'dtype': 1,
'shape': [1, 2048, 7, 7]
},
'res5c_branch2c2': {
'dtype': 1,
'shape': [1, 2048, 7, 7]
}
}
rest_url = 'http://localhost:5563/v1/models/resnet/versions/4/metadata'
response_v4 = get_model_metadata_response_rest(rest_url)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_v4)
assert model_name == response_v4.model_spec.name
assert expected_input_metadata_v4 == input_metadata_v4
assert expected_output_metadata_v4 == output_metadata_v4
shutil.rmtree(resnet_v2_copy_dir)
shutil.rmtree(resnet_v1_copy_dir)
shutil.rmtree(resnet_2_out_copy_dir)
def test_latest_version_rest(self, download_two_model_versions,
get_test_dir,
start_server_update_flow_latest):
resnet_v1, resnet_v2 = download_two_model_versions
dir = get_test_dir + '/saved_models/' + 'update/'
resnet_v1_copy_dir = copy_model(resnet_v1, 1, dir)
time.sleep(8)
print("Getting info about resnet model")
model_name = 'resnet'
out_name = 'resnet_v1_50/predictions/Reshape_1'
expected_input_metadata = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata = {out_name: {'dtype': 1, 'shape': [1, 1000]}}
rest_url = 'http://localhost:5562/v1/models/resnet/metadata'
response = get_model_metadata_response_rest(rest_url)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata == input_metadata
assert expected_output_metadata == output_metadata
# Model status check before update
rest_status_url = 'http://localhost:5562/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
version_status = versions_statuses[0]
assert len(versions_statuses) == 1
assert version_status.version == 1
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v1_copy_dir)
resnet_v2_copy_dir = copy_model(resnet_v2, 2, dir)
time.sleep(10)
out_name = 'resnet_v2_50/predictions/Reshape_1'
expected_input_metadata = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata = {out_name: {'dtype': 1, 'shape': [1, 1001]}}
response = get_model_metadata_response_rest(rest_url)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata == input_metadata
assert expected_output_metadata == output_metadata
# Model status check after update
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 2]
if version_status.version == 1:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 2:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v2_copy_dir)
time.sleep(10)
def test_specific_version(self, download_two_model_versions,
resnet_2_out_model_downloader, get_test_dir,
start_server_update_flow_specific,
create_grpc_channel):
resnet_v1, resnet_v2 = download_two_model_versions
resnet_2_out = resnet_2_out_model_downloader
dir = get_test_dir + '/saved_models/' + 'update/'
stub = create_grpc_channel('localhost:9008', PREDICTION_SERVICE)
status_stub = create_grpc_channel('localhost:9008', MODEL_SERVICE)
resnet_v1_copy_dir = copy_model(resnet_v1, 1, dir)
resnet_2_out_copy_dir = copy_model(resnet_2_out, 4, dir)
time.sleep(8)
# Available versions: 1, 4
print("Getting info about resnet model")
model_name = 'resnet'
out_name_v1 = 'resnet_v1_50/predictions/Reshape_1'
expected_input_metadata_v1 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name_v1: {
'dtype': 1,
'shape': [1, 1000]
}
}
request = get_model_metadata(model_name=model_name, version=1)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
request_latest = get_model_metadata(model_name=model_name)
response_latest = stub.GetModelMetadata(request_latest, 10)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
request_v4 = get_model_metadata(model_name=model_name, version=4)
response_v4 = stub.GetModelMetadata(request_v4, 10)
print("response", response_v4)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_latest)
assert response_v4.model_spec.name == response_latest.model_spec.name
assert input_metadata_v4 == input_metadata_latest
assert output_metadata_v4 == output_metadata_latest
# Model status check
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_2_out_copy_dir)
resnet_v2_copy_dir = copy_model(resnet_v2, 3, dir)
time.sleep(10)
# Available versions: 1, 3
request_latest = get_model_metadata(model_name=model_name)
response_latest = stub.GetModelMetadata(request_latest, 10)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
request_v3 = get_model_metadata(model_name=model_name, version=3)
response_v3 = stub.GetModelMetadata(request_v3, 10)
print("response", response_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert response_v3.model_spec.name == response_latest.model_spec.name
assert input_metadata_v3 == input_metadata_latest
assert output_metadata_v3 == output_metadata_latest
# Model status check
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
if version_status.version == 4:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 1 or version_status.version == 3:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
# Available versions: 1, 3, 4
resnet_2_out_copy_dir = copy_model(resnet_2_out, 4, dir)
time.sleep(10)
request_v1 = get_model_metadata(model_name=model_name, version=1)
response_v1 = stub.GetModelMetadata(request_v1, 10)
input_metadata_v1, output_metadata_v1 = model_metadata_response(
response=response_v1)
assert model_name == response_v1.model_spec.name
assert expected_input_metadata_v1 == input_metadata_v1
assert expected_output_metadata_v1 == output_metadata_v1
out_name_v3 = 'resnet_v2_50/predictions/Reshape_1'
expected_input_metadata_v3 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v3 = {
out_name_v3: {
'dtype': 1,
'shape': [1, 1001]
}
}
request_v3 = get_model_metadata(model_name=model_name, version=3)
response_v3 = stub.GetModelMetadata(request_v3, 10)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert model_name == response_v3.model_spec.name
assert expected_input_metadata_v3 == input_metadata_v3
assert expected_output_metadata_v3 == output_metadata_v3
expected_input_metadata_v4 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v4 = {
'res5c_branch2c1': {
'dtype': 1,
'shape': [1, 2048, 7, 7]
},
'res5c_branch2c2': {
'dtype': 1,
'shape': [1, 2048, 7, 7]
}
}
request_v4 = get_model_metadata(model_name=model_name)
response_v4 = stub.GetModelMetadata(request_v4, 10)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_v4)
assert model_name == response_v4.model_spec.name
assert expected_input_metadata_v4 == input_metadata_v4
assert expected_output_metadata_v4 == output_metadata_v4
# Model status check
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v2_copy_dir)
shutil.rmtree(resnet_v1_copy_dir)
shutil.rmtree(resnet_2_out_copy_dir)
time.sleep(10)
def test_specific_version_rest(self, download_two_model_versions,
resnet_2_out_model_downloader, get_test_dir,
start_server_update_flow_specific):
resnet_v1, resnet_v2 = download_two_model_versions
resnet_2_out = resnet_2_out_model_downloader
dir = get_test_dir + '/saved_models/' + 'update/'
resnet_v1_copy_dir = copy_model(resnet_v1, 1, dir)
resnet_2_out_copy_dir = copy_model(resnet_2_out, 4, dir)
time.sleep(8)
# Available versions: 1, 4
print("Getting info about resnet model")
model_name = 'resnet'
out_name_v1 = 'resnet_v1_50/predictions/Reshape_1'
expected_input_metadata_v1 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v1 = {
out_name_v1: {
'dtype': 1,
'shape': [1, 1000]
}
}
rest_url_latest = 'http://localhost:5563/v1/models/resnet/' \
'versions/1/metadata'
response = get_model_metadata_response_rest(rest_url_latest)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata_v1 == input_metadata
assert expected_output_metadata_v1 == output_metadata
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_latest = get_model_metadata_response_rest(rest_url)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
rest_url_v4 = 'http://localhost:5563/v1/models/resnet/' \
'versions/1/metadata'
response_v4 = get_model_metadata_response_rest(rest_url_v4)
print("response", response_v4)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_latest)
assert response_v4.model_spec.name == response_latest.model_spec.name
assert input_metadata_v4 == input_metadata_latest
assert output_metadata_v4 == output_metadata_latest
# Model status check
rest_status_url = 'http://localhost:5563/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_2_out_copy_dir)
resnet_v2_copy_dir = copy_model(resnet_v2, 3, dir)
time.sleep(10)
# Available versions: 1, 3
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_latest = get_model_metadata_response_rest(rest_url)
print("response", response_latest)
input_metadata_latest, output_metadata_latest = \
model_metadata_response(response=response_latest)
rest_url_v3 = 'http://localhost:5563/v1/models/resnet/' \
'versions/3/metadata'
response_v3 = get_model_metadata_response_rest(rest_url_v3)
print("response", response_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert response_v3.model_spec.name == response_latest.model_spec.name
assert input_metadata_v3 == input_metadata_latest
assert output_metadata_v3 == output_metadata_latest
# Model status check
rest_status_url = 'http://localhost:5563/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
if version_status.version == 4:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 1 or version_status.version == 3:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
# Available versions: 1, 3, 4
resnet_2_out_copy_dir = copy_model(resnet_2_out, 4, dir)
time.sleep(10)
rest_url_v1 = 'http://localhost:5563/v1/models/resnet/' \
'versions/1/metadata'
response_v1 = get_model_metadata_response_rest(rest_url_v1)
input_metadata_v1, output_metadata_v1 = model_metadata_response(
response=response_v1)
assert model_name == response_v1.model_spec.name
assert expected_input_metadata_v1 == input_metadata_v1
assert expected_output_metadata_v1 == output_metadata_v1
out_name_v3 = 'resnet_v2_50/predictions/Reshape_1'
expected_input_metadata_v3 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v3 = {
out_name_v3: {
'dtype': 1,
'shape': [1, 1001]
}
}
rest_url_v3 = 'http://localhost:5563/v1/models/resnet/' \
'versions/3/metadata'
response_v3 = get_model_metadata_response_rest(rest_url_v3)
input_metadata_v3, output_metadata_v3 = model_metadata_response(
response=response_v3)
assert model_name == response_v3.model_spec.name
assert expected_input_metadata_v3 == input_metadata_v3
assert expected_output_metadata_v3 == output_metadata_v3
expected_input_metadata_v4 = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata_v4 = {
'res5c_branch2c1': {
'dtype': 1,
'shape': [1, 2048, 7, 7]
},
'res5c_branch2c2': {
'dtype': 1,
'shape': [1, 2048, 7, 7]
}
}
rest_url = 'http://localhost:5563/v1/models/resnet/metadata'
response_v4 = get_model_metadata_response_rest(rest_url)
input_metadata_v4, output_metadata_v4 = model_metadata_response(
response=response_v4)
assert model_name == response_v4.model_spec.name
assert expected_input_metadata_v4 == input_metadata_v4
assert expected_output_metadata_v4 == output_metadata_v4
# Model status check
rest_status_url = 'http://localhost:5563/v1/models/resnet'
status_response = get_model_status_response_rest(rest_status_url)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 3
for version_status in versions_statuses:
assert version_status.version in [1, 3, 4]
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v2_copy_dir)
shutil.rmtree(resnet_v1_copy_dir)
shutil.rmtree(resnet_2_out_copy_dir)
time.sleep(10)
def test_latest_version(self, download_two_model_versions, get_test_dir,
start_server_update_flow_latest,
create_grpc_channel):
resnet_v1, resnet_v2 = download_two_model_versions
dir = get_test_dir + '/saved_models/' + 'update/'
resnet_v1_copy_dir = copy_model(resnet_v1, 1, dir)
time.sleep(8)
stub = create_grpc_channel('localhost:9007', PREDICTION_SERVICE)
status_stub = create_grpc_channel('localhost:9007', MODEL_SERVICE)
print("Getting info about resnet model")
model_name = 'resnet'
out_name = 'resnet_v1_50/predictions/Reshape_1'
expected_input_metadata = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata = {out_name: {'dtype': 1, 'shape': [1, 1000]}}
request = get_model_metadata(model_name=model_name)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata == input_metadata
assert expected_output_metadata == output_metadata
# Model status check before update
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
version_status = versions_statuses[0]
assert len(versions_statuses) == 1
assert version_status.version == 1
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v1_copy_dir)
resnet_v2_copy_dir = copy_model(resnet_v2, 2, dir)
time.sleep(10)
out_name = 'resnet_v2_50/predictions/Reshape_1'
expected_input_metadata = {
'input': {
'dtype': 1,
'shape': [1, 3, 224, 224]
}
}
expected_output_metadata = {out_name: {'dtype': 1, 'shape': [1, 1001]}}
request = get_model_metadata(model_name=model_name)
response = stub.GetModelMetadata(request, 10)
input_metadata, output_metadata = model_metadata_response(
response=response)
print(output_metadata)
assert model_name == response.model_spec.name
assert expected_input_metadata == input_metadata
assert expected_output_metadata == output_metadata
# Model status check after update
model_name = 'resnet'
request = get_model_status(model_name=model_name)
status_response = status_stub.GetModelStatus(request, 10)
versions_statuses = status_response.model_version_status
assert len(versions_statuses) == 2
for version_status in versions_statuses:
assert version_status.version in [1, 2]
if version_status.version == 1:
assert version_status.state == ModelVersionState.END
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.END][ErrorCode.OK]
elif version_status.version == 2:
assert version_status.state == ModelVersionState.AVAILABLE
assert version_status.status.error_code == ErrorCode.OK
assert version_status.status.error_message == _ERROR_MESSAGE[
ModelVersionState.AVAILABLE][ErrorCode.OK]
###
shutil.rmtree(resnet_v2_copy_dir)
time.sleep(10)
