完成预测模型的grpc服务

__init__.py

@@ -0,0 +1,4 @@
+import sys
+import os
+
+sys.path.append(".")

api/predict.proto

@@ -0,0 +1,39 @@
+syntax = "proto3";  
+
+service Predict {
+    rpc PayDay(RequestPay) returns (ReplyPay) {}
+    rpc GiftDay(RequestGift) returns (ReplyGift) {}
+}
+
+// Request 统一Request请求
+message RequestPay {
+    // count, total_coin / last_total_coin, total_coin  // 24小时
+    int32 Hour = 1;
+    int64 Coin = 2;
+    int64 YesterdayCoin = 3;
+}
+
+// RequestGift 统一Request请求
+message RequestGift {
+     // count, total_coin / last_total_coin, total_coin  // 24小时
+     int32 Hour = 1;
+     int64 Coin = 2;
+     int64 YesterdayCoin = 3;
+}
+
+// ReplyHeader 统一ReplyHeader 响应
+message ReplyHeader {
+    int32 Code = 1;
+    string Message = 2;
+} 
+
+message ReplyPay {
+    ReplyHeader Header = 1;
+    int64 Result = 2;
+}
+
+
+message ReplyGift {
+    ReplyHeader Header = 1;
+    int64 Result = 2;
+}

data.py

@@ -85,6 +85,7 @@ def get_collect():
  
 def load_pay_data(textNum = 80):
  
+
     collect = get_collect()
  
     # TODO: 处理gift pay的波动关系
@@ -101,6 +102,7 @@ def load_pay_data(textNum = 80):
     for cur_v in collect_pay[1:]:
     
         total_coin = 0
+        users = 0
         last_total_coin = 0
 
         for v2 in lastday_v:
@@ -109,6 +111,7 @@ def load_pay_data(textNum = 80):
         count = 0
         for v1, v2 in zip(cur_v,lastday_v):
             total_coin += v1[0] + v1[1]
+            users += v1[2]
             # print(v1[3])
     
             # last_total_coin += v2[0] + v2[1]
@@ -116,7 +119,8 @@ def load_pay_data(textNum = 80):
             # compare = float(total_coin - last_total_coin) / float(last_total_coin)
             # print(compare)
     
-            x_train.append([count, total_coin, total_coin/last_total_coin])
+            # 时刻. 前一个小时 时刻. 当前支付总币数. 当前支付总币数 昨天币数
+            x_train.append([count  ,total_coin / last_total_coin , total_coin])
             count+=1
 
         for i in range(count):
@@ -124,7 +128,8 @@ def load_pay_data(textNum = 80):
 
         lastday_v = cur_v
 
-    x_train = numpy.reshape(x_train, (len(x_train) , 3, 1))
+    input_shape = (len(x_train[0]), 1)
+    x_train = numpy.reshape(x_train, (len(x_train) , input_shape[0], input_shape[1]))
     y_train = numpy.reshape(y_train, (len(y_train)))
     # max_features = 1024
 
@@ -134,7 +139,7 @@ def load_pay_data(textNum = 80):
     # x_train = x_train[:len(x_train) - textNum]
     # y_train = y_train[:len(y_train) - textNum]
 
-    return x_train, y_train, tx_train, ty_train
+    return x_train, y_train, tx_train, ty_train, input_shape
 
 def load_gift_data(textNum = 80):
 
@@ -159,7 +164,7 @@ def load_gift_data(textNum = 80):
             last_total_coin += v2[0]  
 
         f = 20000000.0
-        count = 1
+        count = 0
         for v1, v2 in zip(cur_v,lastday_v):
             total_coin += v1[0] 
             # print(v1[3])
@@ -170,16 +175,17 @@ def load_gift_data(textNum = 80):
             # print(v2[3])
             # compare = float(total_coin - last_total_coin) / float(last_total_coin)
             # print(compare)
-
+            # 参数  前一小个小时. 时刻. 当前金钱. 送礼人数
-            x_train.append([count, total_coin, total_coin / last_total_coin, users ])
+            x_train.append([count, total_coin / last_total_coin,  total_coin ])
             count+=1
 
-        for i in range(count - 1):
+        for i in range(count):
             y_train.append(total_coin)
 
         lastday_v = cur_v
 
-    x_train = numpy.reshape(x_train, (len(x_train) , 4, 1))
+    input_shape = (len(x_train[0]), 1)
+    x_train = numpy.reshape(x_train, (len(x_train) , input_shape[0], input_shape[1]))
     y_train = numpy.reshape(y_train, (len(y_train)))
     # max_features = 1024
 
@@ -189,4 +195,4 @@ def load_gift_data(textNum = 80):
     # x_train = x_train[:len(x_train) - textNum]
     # y_train = y_train[:len(y_train) - textNum]
 
-    return x_train, y_train, tx_train, ty_train
+    return x_train, y_train, tx_train, ty_train, input_shape

example.py

@@ -1 +0,0 @@
- 

gen_proto3.sh

@@ -0,0 +1,3 @@
+#! /bin/bash
+PBPATH=./api
+python -m grpc_tools.protoc -I$PBPATH  --python_out=. --grpc_python_out=. $PBPATH/*.proto

grpc_client.py

@@ -0,0 +1,20 @@
+import grpc
+import logging
+import predict_pb2, predict_pb2_grpc
+ 
+
+def run():
+    option = [('grpc.keepalive_timeout_ms', 10000)]
+    with grpc.insecure_channel(target='localhost:50051', options=option) as channel:  
+        stub = predict_pb2_grpc.PredictStub(channel)
+       
+        response = stub.PayDay( predict_pb2.RequestPay(Hour=0,Coin=100,YesterdayCoin=100), timeout=10)
+        print(response, type(response.Header.Code))
+
+        response = stub.GiftDay(predict_pb2.RequestGift(Hour=0,Coin=100,YesterdayCoin=100), timeout=10)
+        print(response, type(response.Header.Code))
+
+
+if __name__ == '__main__':
+    logging.basicConfig()
+    run()

grpc_server.py

@@ -0,0 +1,39 @@
+ 
+
+import grpc
+import logging
+from concurrent import futures
+ 
+import predict_pb2, predict_pb2_grpc
+from predict_pb2 import *
+from predict_pb2_grpc import *
+
+import numpy
+from keras.models import load_model
+from data import load_pay_data, load_gift_data
+pay_model = load_model("./predict_pay")
+gift_model = load_model("./predict_gift")
+ 
+class Predict(predict_pb2_grpc.PredictServicer):
+    def PayDay(self, request, context):
+        # print(request)
+        inputx = numpy.reshape([request.Hour, request.Coin / request.YesterdayCoin, request.Coin], (1, 3, 1)) 
+        predict_value = pay_model.predict(inputx)
+        return ReplyPay(Header=ReplyHeader(Code=0, Message=""), Result=int(predict_value[0][0]))
+        # return super().PayDay(request, context)
+    def GiftDay(self, request, context):
+        # print(request)
+        inputx = numpy.reshape([request.Hour, request.Coin / request.YesterdayCoin, request.Coin], (1, 3, 1)) 
+        predict_value = gift_model.predict(inputx)
+        return ReplyGift(Header=ReplyHeader(Code=0, Message=""), Result=int(predict_value[0][0]))
+
+def server():
+    grpc_server = grpc.server(futures.ThreadPoolExecutor(max_workers=2))
+    predict_pb2_grpc.add_PredictServicer_to_server(Predict(), grpc_server)
+    grpc_server.add_insecure_port('[::]:50051')
+    grpc_server.start()
+    grpc_server.wait_for_termination()
+
+if __name__ == '__main__':
+    logging.basicConfig()
+    server()

predict.proto

@@ -1,24 +0,0 @@
-syntax = "proto3";
-
-service Predict {
-    rpc PayDay(RequestPay) returns (Reply) {}
-    rpc GiftDay(RequestGift) returns (Reply) {}
-}
-
-// Request 统一Request请求
-message RequestPay {
-    // count, total_coin , (total_coin - last_total_coin) , v1[2] , v2[2]] // 24小时
-    int32 Hour = 1;
-    int64 Coin = 2;
-    int64 YesterdayCoin = 3;
-}
-
-// RequestGift 统一Request请求
-message RequestGift {
- 
-}
-
-// Reply 统一Reply 响应
-message Reply {
-
-} 

predict.py

@@ -5,7 +5,7 @@ from data import load_pay_data, load_gift_data
 import matplotlib.pyplot as plt
 
 
-# x_train, y_train, tx_train, ty_train = load_pay_data(160)
+# x_train, y_train, tx_train, ty_train, _ = load_pay_data(160)
 # model = load_model("./predict_pay")
 
 # p_data = model.predict(tx_train)
@@ -16,7 +16,7 @@ import matplotlib.pyplot as plt
 #         print("测结果:", p_data[i][0], "测:", tx_train[i], "真实:", ty_train[i])    
 
 
-x_train, y_train, tx_train, ty_train = load_gift_data(160)
+x_train, y_train, tx_train, ty_train, _ = load_gift_data(160)
 model = load_model("./predict_gift")
 p_data = model.predict(tx_train)
 for i in range(len(p_data)):

predict_pb2.py

@@ -0,0 +1,317 @@
+# -*- coding: utf-8 -*-
+# Generated by the protocol buffer compiler.  DO NOT EDIT!
+# source: predict.proto
+"""Generated protocol buffer code."""
+from google.protobuf import descriptor as _descriptor
+from google.protobuf import message as _message
+from google.protobuf import reflection as _reflection
+from google.protobuf import symbol_database as _symbol_database
+# @@protoc_insertion_point(imports)
+
+_sym_db = _symbol_database.Default()
+
+
+
+
+DESCRIPTOR = _descriptor.FileDescriptor(
+  name='predict.proto',
+  package='',
+  syntax='proto3',
+  serialized_options=None,
+  create_key=_descriptor._internal_create_key,
+  serialized_pb=b'\n\rpredict.proto\"?\n\nRequestPay\x12\x0c\n\x04Hour\x18\x01 \x01(\x05\x12\x0c\n\x04\x43oin\x18\x02 \x01(\x03\x12\x15\n\rYesterdayCoin\x18\x03 \x01(\x03\"@\n\x0bRequestGift\x12\x0c\n\x04Hour\x18\x01 \x01(\x05\x12\x0c\n\x04\x43oin\x18\x02 \x01(\x03\x12\x15\n\rYesterdayCoin\x18\x03 \x01(\x03\",\n\x0bReplyHeader\x12\x0c\n\x04\x43ode\x18\x01 \x01(\x05\x12\x0f\n\x07Message\x18\x02 \x01(\t\"8\n\x08ReplyPay\x12\x1c\n\x06Header\x18\x01 \x01(\x0b\x32\x0c.ReplyHeader\x12\x0e\n\x06Result\x18\x02 \x01(\x03\"9\n\tReplyGift\x12\x1c\n\x06Header\x18\x01 \x01(\x0b\x32\x0c.ReplyHeader\x12\x0e\n\x06Result\x18\x02 \x01(\x03\x32T\n\x07Predict\x12\"\n\x06PayDay\x12\x0b.RequestPay\x1a\t.ReplyPay\"\x00\x12%\n\x07GiftDay\x12\x0c.RequestGift\x1a\n.ReplyGift\"\x00\x62\x06proto3'
+)
+
+
+
+
+_REQUESTPAY = _descriptor.Descriptor(
+  name='RequestPay',
+  full_name='RequestPay',
+  filename=None,
+  file=DESCRIPTOR,
+  containing_type=None,
+  create_key=_descriptor._internal_create_key,
+  fields=[
+    _descriptor.FieldDescriptor(
+      name='Hour', full_name='RequestPay.Hour', index=0,
+      number=1, type=5, cpp_type=1, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='Coin', full_name='RequestPay.Coin', index=1,
+      number=2, type=3, cpp_type=2, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='YesterdayCoin', full_name='RequestPay.YesterdayCoin', index=2,
+      number=3, type=3, cpp_type=2, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+  ],
+  extensions=[
+  ],
+  nested_types=[],
+  enum_types=[
+  ],
+  serialized_options=None,
+  is_extendable=False,
+  syntax='proto3',
+  extension_ranges=[],
+  oneofs=[
+  ],
+  serialized_start=17,
+  serialized_end=80,
+)
+
+
+_REQUESTGIFT = _descriptor.Descriptor(
+  name='RequestGift',
+  full_name='RequestGift',
+  filename=None,
+  file=DESCRIPTOR,
+  containing_type=None,
+  create_key=_descriptor._internal_create_key,
+  fields=[
+    _descriptor.FieldDescriptor(
+      name='Hour', full_name='RequestGift.Hour', index=0,
+      number=1, type=5, cpp_type=1, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='Coin', full_name='RequestGift.Coin', index=1,
+      number=2, type=3, cpp_type=2, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='YesterdayCoin', full_name='RequestGift.YesterdayCoin', index=2,
+      number=3, type=3, cpp_type=2, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+  ],
+  extensions=[
+  ],
+  nested_types=[],
+  enum_types=[
+  ],
+  serialized_options=None,
+  is_extendable=False,
+  syntax='proto3',
+  extension_ranges=[],
+  oneofs=[
+  ],
+  serialized_start=82,
+  serialized_end=146,
+)
+
+
+_REPLYHEADER = _descriptor.Descriptor(
+  name='ReplyHeader',
+  full_name='ReplyHeader',
+  filename=None,
+  file=DESCRIPTOR,
+  containing_type=None,
+  create_key=_descriptor._internal_create_key,
+  fields=[
+    _descriptor.FieldDescriptor(
+      name='Code', full_name='ReplyHeader.Code', index=0,
+      number=1, type=5, cpp_type=1, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='Message', full_name='ReplyHeader.Message', index=1,
+      number=2, type=9, cpp_type=9, label=1,
+      has_default_value=False, default_value=b"".decode('utf-8'),
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+  ],
+  extensions=[
+  ],
+  nested_types=[],
+  enum_types=[
+  ],
+  serialized_options=None,
+  is_extendable=False,
+  syntax='proto3',
+  extension_ranges=[],
+  oneofs=[
+  ],
+  serialized_start=148,
+  serialized_end=192,
+)
+
+
+_REPLYPAY = _descriptor.Descriptor(
+  name='ReplyPay',
+  full_name='ReplyPay',
+  filename=None,
+  file=DESCRIPTOR,
+  containing_type=None,
+  create_key=_descriptor._internal_create_key,
+  fields=[
+    _descriptor.FieldDescriptor(
+      name='Header', full_name='ReplyPay.Header', index=0,
+      number=1, type=11, cpp_type=10, label=1,
+      has_default_value=False, default_value=None,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='Result', full_name='ReplyPay.Result', index=1,
+      number=2, type=3, cpp_type=2, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+  ],
+  extensions=[
+  ],
+  nested_types=[],
+  enum_types=[
+  ],
+  serialized_options=None,
+  is_extendable=False,
+  syntax='proto3',
+  extension_ranges=[],
+  oneofs=[
+  ],
+  serialized_start=194,
+  serialized_end=250,
+)
+
+
+_REPLYGIFT = _descriptor.Descriptor(
+  name='ReplyGift',
+  full_name='ReplyGift',
+  filename=None,
+  file=DESCRIPTOR,
+  containing_type=None,
+  create_key=_descriptor._internal_create_key,
+  fields=[
+    _descriptor.FieldDescriptor(
+      name='Header', full_name='ReplyGift.Header', index=0,
+      number=1, type=11, cpp_type=10, label=1,
+      has_default_value=False, default_value=None,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+    _descriptor.FieldDescriptor(
+      name='Result', full_name='ReplyGift.Result', index=1,
+      number=2, type=3, cpp_type=2, label=1,
+      has_default_value=False, default_value=0,
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      serialized_options=None, file=DESCRIPTOR,  create_key=_descriptor._internal_create_key),
+  ],
+  extensions=[
+  ],
+  nested_types=[],
+  enum_types=[
+  ],
+  serialized_options=None,
+  is_extendable=False,
+  syntax='proto3',
+  extension_ranges=[],
+  oneofs=[
+  ],
+  serialized_start=252,
+  serialized_end=309,
+)
+
+_REPLYPAY.fields_by_name['Header'].message_type = _REPLYHEADER
+_REPLYGIFT.fields_by_name['Header'].message_type = _REPLYHEADER
+DESCRIPTOR.message_types_by_name['RequestPay'] = _REQUESTPAY
+DESCRIPTOR.message_types_by_name['RequestGift'] = _REQUESTGIFT
+DESCRIPTOR.message_types_by_name['ReplyHeader'] = _REPLYHEADER
+DESCRIPTOR.message_types_by_name['ReplyPay'] = _REPLYPAY
+DESCRIPTOR.message_types_by_name['ReplyGift'] = _REPLYGIFT
+_sym_db.RegisterFileDescriptor(DESCRIPTOR)
+
+RequestPay = _reflection.GeneratedProtocolMessageType('RequestPay', (_message.Message,), {
+  'DESCRIPTOR' : _REQUESTPAY,
+  '__module__' : 'predict_pb2'
+  # @@protoc_insertion_point(class_scope:RequestPay)
+  })
+_sym_db.RegisterMessage(RequestPay)
+
+RequestGift = _reflection.GeneratedProtocolMessageType('RequestGift', (_message.Message,), {
+  'DESCRIPTOR' : _REQUESTGIFT,
+  '__module__' : 'predict_pb2'
+  # @@protoc_insertion_point(class_scope:RequestGift)
+  })
+_sym_db.RegisterMessage(RequestGift)
+
+ReplyHeader = _reflection.GeneratedProtocolMessageType('ReplyHeader', (_message.Message,), {
+  'DESCRIPTOR' : _REPLYHEADER,
+  '__module__' : 'predict_pb2'
+  # @@protoc_insertion_point(class_scope:ReplyHeader)
+  })
+_sym_db.RegisterMessage(ReplyHeader)
+
+ReplyPay = _reflection.GeneratedProtocolMessageType('ReplyPay', (_message.Message,), {
+  'DESCRIPTOR' : _REPLYPAY,
+  '__module__' : 'predict_pb2'
+  # @@protoc_insertion_point(class_scope:ReplyPay)
+  })
+_sym_db.RegisterMessage(ReplyPay)
+
+ReplyGift = _reflection.GeneratedProtocolMessageType('ReplyGift', (_message.Message,), {
+  'DESCRIPTOR' : _REPLYGIFT,
+  '__module__' : 'predict_pb2'
+  # @@protoc_insertion_point(class_scope:ReplyGift)
+  })
+_sym_db.RegisterMessage(ReplyGift)
+
+
+
+_PREDICT = _descriptor.ServiceDescriptor(
+  name='Predict',
+  full_name='Predict',
+  file=DESCRIPTOR,
+  index=0,
+  serialized_options=None,
+  create_key=_descriptor._internal_create_key,
+  serialized_start=311,
+  serialized_end=395,
+  methods=[
+  _descriptor.MethodDescriptor(
+    name='PayDay',
+    full_name='Predict.PayDay',
+    index=0,
+    containing_service=None,
+    input_type=_REQUESTPAY,
+    output_type=_REPLYPAY,
+    serialized_options=None,
+    create_key=_descriptor._internal_create_key,
+  ),
+  _descriptor.MethodDescriptor(
+    name='GiftDay',
+    full_name='Predict.GiftDay',
+    index=1,
+    containing_service=None,
+    input_type=_REQUESTGIFT,
+    output_type=_REPLYGIFT,
+    serialized_options=None,
+    create_key=_descriptor._internal_create_key,
+  ),
+])
+_sym_db.RegisterServiceDescriptor(_PREDICT)
+
+DESCRIPTOR.services_by_name['Predict'] = _PREDICT
+
+# @@protoc_insertion_point(module_scope)

predict_pb2_grpc.py

@@ -0,0 +1,99 @@
+# Generated by the gRPC Python protocol compiler plugin. DO NOT EDIT!
+"""Client and server classes corresponding to protobuf-defined services."""
+import grpc
+
+import predict_pb2 as predict__pb2
+
+
+class PredictStub(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def __init__(self, channel):
+        """Constructor.
+
+        Args:
+            channel: A grpc.Channel.
+        """
+        self.PayDay = channel.unary_unary(
+                '/Predict/PayDay',
+                request_serializer=predict__pb2.RequestPay.SerializeToString,
+                response_deserializer=predict__pb2.ReplyPay.FromString,
+                )
+        self.GiftDay = channel.unary_unary(
+                '/Predict/GiftDay',
+                request_serializer=predict__pb2.RequestGift.SerializeToString,
+                response_deserializer=predict__pb2.ReplyGift.FromString,
+                )
+
+
+class PredictServicer(object):
+    """Missing associated documentation comment in .proto file."""
+
+    def PayDay(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+    def GiftDay(self, request, context):
+        """Missing associated documentation comment in .proto file."""
+        context.set_code(grpc.StatusCode.UNIMPLEMENTED)
+        context.set_details('Method not implemented!')
+        raise NotImplementedError('Method not implemented!')
+
+
+def add_PredictServicer_to_server(servicer, server):
+    rpc_method_handlers = {
+            'PayDay': grpc.unary_unary_rpc_method_handler(
+                    servicer.PayDay,
+                    request_deserializer=predict__pb2.RequestPay.FromString,
+                    response_serializer=predict__pb2.ReplyPay.SerializeToString,
+            ),
+            'GiftDay': grpc.unary_unary_rpc_method_handler(
+                    servicer.GiftDay,
+                    request_deserializer=predict__pb2.RequestGift.FromString,
+                    response_serializer=predict__pb2.ReplyGift.SerializeToString,
+            ),
+    }
+    generic_handler = grpc.method_handlers_generic_handler(
+            'Predict', rpc_method_handlers)
+    server.add_generic_rpc_handlers((generic_handler,))
+
+
+ # This class is part of an EXPERIMENTAL API.
+class Predict(object):
+    """Missing associated documentation comment in .proto file."""
+
+    @staticmethod
+    def PayDay(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/Predict/PayDay',
+            predict__pb2.RequestPay.SerializeToString,
+            predict__pb2.ReplyPay.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)
+
+    @staticmethod
+    def GiftDay(request,
+            target,
+            options=(),
+            channel_credentials=None,
+            call_credentials=None,
+            insecure=False,
+            compression=None,
+            wait_for_ready=None,
+            timeout=None,
+            metadata=None):
+        return grpc.experimental.unary_unary(request, target, '/Predict/GiftDay',
+            predict__pb2.RequestGift.SerializeToString,
+            predict__pb2.ReplyGift.FromString,
+            options, channel_credentials,
+            insecure, call_credentials, compression, wait_for_ready, timeout, metadata)

requirements.txt

@@ -2,3 +2,4 @@ tensorflow
 keras
 numpy
 pymysql
+grpc_tools

train_gift.py

@@ -15,12 +15,12 @@ from data import load_gift_data
 
 if __name__ == "__main__":
 
-    x_train, y_train, tx_train, ty_train = load_gift_data()
+    x_train, y_train, tx_train, ty_train, input_shape = load_gift_data()
 
     model = Sequential()
     units = 400 
     
-    model.add(LSTM(units, activation='relu', input_shape=(4,1) ))
+    model.add(LSTM(units, activation='relu', input_shape=input_shape ))
     model.add(Dropout(0.2))
  
     model.add(Dense(1))
@@ -28,7 +28,7 @@ if __name__ == "__main__":
     
     model.compile(loss='mse', optimizer='adam')
 
-    model.fit(x_train, y_train, batch_size=1, epochs=50)
+    model.fit(x_train, y_train, batch_size=128, epochs=1500)
     model.save("./predict_gift")
 
     p_data = model.predict(tx_train)

train_pay.py

@@ -5,6 +5,7 @@ from  keras.layers import Dense, Dropout, Embedding
 from  keras.layers import InputLayer
 from  keras.layers import LSTM
 from  keras import backend 
+from keras.layers.recurrent import SimpleRNN
 
 import pymysql
 import pickle
@@ -16,18 +17,20 @@ from data import load_pay_data
 
 if __name__ == "__main__":
 
-    x_train, y_train, tx_train, ty_train = load_pay_data(80)
+    x_train, y_train, tx_train, ty_train, input_shape = load_pay_data(80)
 
     
     model = Sequential()
     units = 500
-    model.add(LSTM(units, activation='relu', input_shape=(3,1)))
+    model.add(LSTM(units, activation='relu', dropout=0.1, input_shape=input_shape))
-    model.add(Dropout(0.3))
+    
+    # model.add(SimpleRNN(units, activation='relu'))
+    # model.add(Dropout(0.1))
     model.add(Dense(1))
     model.summary()
-    model.compile(loss='mse', optimizer='adam')
+    model.compile(loss = 'mse', optimizer = 'adam')
 
-    model.fit(x_train, y_train, batch_size=1, epochs=50)
+    model.fit(x_train, y_train, batch_size=96, epochs=1200)
     model.save("./predict_pay")
 
     p_data = model.predict(tx_train)