def test_add():
channel = grpc.insecure_channel('localhost:5500')
stub = ms_service_pb2_grpc.MSServiceStub(channel)
request = ms_service_pb2.PredictRequest()
x = request.data.add()
x.tensor_shape.dims.extend([4])
x.tensor_type = ms_service_pb2.MS_FLOAT32
x.data = (np.ones([4]).astype(np.float32)).tobytes()
y = request.data.add()
y.tensor_shape.dims.extend([4])
y.tensor_type = ms_service_pb2.MS_FLOAT32
y.data = (np.ones([4]).astype(np.float32)).tobytes()
result = stub.Predict(request)
result_np = np.frombuffer(result.result[0].data, dtype=np.float32).reshape(
result.result[0].tensor_shape.dims)
print("ms client received: ")
print(result_np)
net = AddNet()
net_out = net(Tensor(np.ones([4]).astype(np.float32)),
Tensor(np.ones([4]).astype(np.float32)))
print("add net out: ")
print(net_out)
assert np.allclose(net_out.asnumpy(),
result_np,
0.001,
0.001,
equal_nan=True)
def generate(s='', data_type=0):
"""generate"""
if len(sys.argv) > 2:
sys.exit("input error")
channel_str = ""
if len(sys.argv) == 2:
split_args = sys.argv[1].split('=')
if len(split_args) > 1:
channel_str = split_args[1]
else:
channel_str = 'localhost:5500'
else:
channel_str = 'localhost:5500'
serving_channel = grpc.insecure_channel(channel_str)
stub_func = ms_service_pb2_grpc.MSServiceStub(serving_channel)
request_module = ms_service_pb2.PredictRequest()
_target_ids = np.ones(shape=(1, 128))
_segment_ids = np.ones(shape=(1, 128))
pad_mask = np.ones(shape=(1, 128))
request_module, request_input_ids, request_segment_ids, request_pad_mask = input_construction(\
request_module, _target_ids, _segment_ids, pad_mask)
if data_type in [0, 1]:
poetry = generate_random_poetry(s, stub_func, request_module, request_input_ids,\
request_segment_ids, request_pad_mask)
else:
poetry = generate_hidden(s, stub_func, request_module,
request_input_ids, request_segment_ids,
request_pad_mask)
print(poetry)
return poetry
def test_bert():
MAX_MESSAGE_LENGTH = 0x7fffffff
input_ids = np.random.randint(0, 1000, size=(2, 32), dtype=np.int32)
segment_ids = np.zeros((2, 32), dtype=np.int32)
input_mask = np.zeros((2, 32), dtype=np.int32)
channel = grpc.insecure_channel(
'localhost:5500',
options=[('grpc.max_send_message_length', MAX_MESSAGE_LENGTH),
('grpc.max_receive_message_length', MAX_MESSAGE_LENGTH)])
stub = ms_service_pb2_grpc.MSServiceStub(channel)
request = ms_service_pb2.PredictRequest()
x = request.data.add()
x.tensor_shape.dims.extend([2, 32])
x.tensor_type = ms_service_pb2.MS_INT32
x.data = input_ids.tobytes()
y = request.data.add()
y.tensor_shape.dims.extend([2, 32])
y.tensor_type = ms_service_pb2.MS_INT32
y.data = segment_ids.tobytes()
z = request.data.add()
z.tensor_shape.dims.extend([2, 32])
z.tensor_type = ms_service_pb2.MS_INT32
z.data = input_mask.tobytes()
result = stub.Predict(request)
result_np = np.frombuffer(result.result[0].data, dtype=np.float32).reshape(
result.result[0].tensor_shape.dims)
print("ms client received: ")
print(result_np)
net = BertModel(bert_net_cfg, False)
bert_out = net(Tensor(input_ids), Tensor(segment_ids), Tensor(input_mask))
print("bert out: ")
print(bert_out)
bert_out_size = len(bert_out)
for i in range(bert_out_size):
result_np = np.frombuffer(result.result[i].data,
dtype=np.float32).reshape(
result.result[i].tensor_shape.dims)
logger.info("i:{}, result_np:{}, bert_out:{}".format(
i, result.result[i].tensor_shape.dims,
bert_out[i].asnumpy().shape))
assert np.allclose(bert_out[i].asnumpy(),
result_np,
0.001,
0.001,
equal_nan=True)
def run():
channel = grpc.insecure_channel('localhost:50051')
stub = ms_service_pb2_grpc.MSServiceStub(channel)
# request = ms_service_pb2.EvalRequest()
# request.name = 'haha'
# response = stub.Eval(request)
# print("ms client received: " + response.message)
request = ms_service_pb2.PredictRequest()
request.data.tensor_shape.dims.extend([32, 1, 32, 32])
request.data.tensor_type = ms_service_pb2.MS_FLOAT32
request.data.data = (np.ones([32, 1, 32, 32]).astype(np.float32) * 0.01).tobytes()
request.label.tensor_shape.dims.extend([32])
request.label.tensor_type = ms_service_pb2.MS_INT32
request.label.data = np.ones([32]).astype(np.int32).tobytes()
result = stub.Test(request)
#result_np = np.frombuffer(result.result.data, dtype=np.float32).reshape(result.result.tensor_shape.dims)
print("ms client test call received: ")
def run():
channel = grpc.insecure_channel('localhost:5500')
stub = ms_service_pb2_grpc.MSServiceStub(channel)
request = ms_service_pb2.PredictRequest()
x = request.data.add()
x.tensor_shape.dims.extend([4])
x.tensor_type = ms_service_pb2.MS_FLOAT32
x.data = (np.ones([4]).astype(np.float32)).tobytes()
y = request.data.add()
y.tensor_shape.dims.extend([4])
y.tensor_type = ms_service_pb2.MS_FLOAT32
y.data = (np.ones([4]).astype(np.float32)).tobytes()
result = stub.Predict(request)
print(result)
result_np = np.frombuffer(result.result[0].data, dtype=np.float32).reshape(
result.result[0].tensor_shape.dims)
print("ms client received: ")
print(result_np)
def run():
if len(sys.argv) > 2:
sys.exit("input error")
channel_str = ""
if len(sys.argv) == 2:
split_args = sys.argv[1].split('=')
if len(split_args) > 1:
channel_str = split_args[1]
else:
channel_str = 'localhost:5500'
else:
channel_str = 'localhost:5500'
channel = grpc.insecure_channel(channel_str)
stub = ms_service_pb2_grpc.MSServiceStub(channel)
request = ms_service_pb2.PredictRequest()
x = request.data.add()
x.tensor_shape.dims.extend([4])
x.tensor_type = ms_service_pb2.MS_FLOAT32
x.data = (np.ones([4]).astype(np.float32)).tobytes()
y = request.data.add()
y.tensor_shape.dims.extend([4])
y.tensor_type = ms_service_pb2.MS_FLOAT32
y.data = (np.ones([4]).astype(np.float32)).tobytes()
try:
result = stub.Predict(request)
print(result)
result_np = np.frombuffer(result.result[0].data,
dtype=np.float32).reshape(
result.result[0].tensor_shape.dims)
print("ms client received: ")
print(result_np)
except grpc.RpcError as e:
print(e.details())
status_code = e.code()
print(status_code.name)
print(status_code.value)
def test_bert():
MAX_MESSAGE_LENGTH = 0x7fffffff
input_ids = np.random.randint(0, 1000, size=(2, 32), dtype=np.int32)
segment_ids = np.zeros((2, 32), dtype=np.int32)
input_mask = np.zeros((2, 32), dtype=np.int32)
# grpc visit
channel = grpc.insecure_channel(
'localhost:5500',
options=[('grpc.max_send_message_length', MAX_MESSAGE_LENGTH),
('grpc.max_receive_message_length', MAX_MESSAGE_LENGTH)])
stub = ms_service_pb2_grpc.MSServiceStub(channel)
request = ms_service_pb2.PredictRequest()
x = request.data.add()
x.tensor_shape.dims.extend([2, 32])
x.tensor_type = ms_service_pb2.MS_INT32
x.data = input_ids.tobytes()
y = request.data.add()
y.tensor_shape.dims.extend([2, 32])
y.tensor_type = ms_service_pb2.MS_INT32
y.data = segment_ids.tobytes()
z = request.data.add()
z.tensor_shape.dims.extend([2, 32])
z.tensor_type = ms_service_pb2.MS_INT32
z.data = input_mask.tobytes()
result = stub.Predict(request)
grpc_result = np.frombuffer(result.result[0].data,
dtype=np.float32).reshape(
result.result[0].tensor_shape.dims)
print("ms grpc client received: ")
print(grpc_result)
# ms result
net = BertModel(bert_net_cfg, False)
bert_out = net(Tensor(input_ids), Tensor(segment_ids), Tensor(input_mask))
print("bert out: ")
print(bert_out[0])
bert_out_size = len(bert_out)
# compare grpc result
for i in range(bert_out_size):
grpc_result = np.frombuffer(result.result[i].data,
dtype=np.float32).reshape(
result.result[i].tensor_shape.dims)
logger.info("i:{}, grpc_result:{}, bert_out:{}".format(
i, result.result[i].tensor_shape.dims,
bert_out[i].asnumpy().shape))
assert np.allclose(bert_out[i].asnumpy(),
grpc_result,
0.001,
0.001,
equal_nan=True)
# http visit
data = {
"tensor":
[input_ids.tolist(),
segment_ids.tolist(),
input_mask.tolist()]
}
url = "http://127.0.0.1:5501"
input_json = json.dumps(data)
headers = {'Content-type': 'application/json'}
response = requests.post(url, data=input_json, headers=headers)
result = response.text
result = result.replace('\r', '\\r').replace('\n', '\\n')
result_json = json.loads(result, strict=False)
http_result = np.array(result_json['tensor'])
print("ms http client received: ")
print(http_result[0][:200])
# compare http result
for i in range(bert_out_size):
logger.info("i:{}, http_result:{}, bert_out:{}".format(
i, np.shape(http_result[i]), bert_out[i].asnumpy().shape))
assert np.allclose(bert_out[i].asnumpy(),
http_result[i],
0.001,
0.001,
equal_nan=True)