如何保存某一层的输出 about paddlerec HOT 8 CLOSED

    def net(self, input, is_infer=False):
        self.label_input = input[0]
        self.sparse_inputs = input[1:self.sparse_inputs_slots]
        self.dense_input = input[-1]

        dnn_model = DNNLayer(
            self.sparse_feature_number,
            self.sparse_feature_dim,
            self.dense_input_dim,
            self.sparse_inputs_slots-1,
            self.fc_sizes,
            sync_mode=self.sync_mode)
        cust_embedding = dnn_model.forward(self.sparse_inputs,
                                           self.dense_input)

        output = paddle.matmul(cust_embedding,dnn_model.embedding[0].weight,transpose_y=True)
        predict = paddle.nn.functional.softmax(output)
        self.predict = predict
        accuracy = paddle.static.accuracy(input=self.predict,
                                              label=self.label_input,
                                              k = 100
                                              )


        self.inference_target_var = accuracy
        if is_infer:
            fetch_dict = {'accuracy': accuracy}
            return fetch_dict

        cost = fluid.layers.sampled_softmax_with_cross_entropy(logits=output,label=self.label_input,num_samples=400)
        avg_cost = paddle.mean(x=cost)
        self._cost = avg_cost
        fetch_dict = {'cost': avg_cost, 'accuracy': accuracy}
        return fetch_dict

prog = paddle.static.default_main_program()
prog.list_vars()

prog = paddle.static.default_main_program()
for var in prog.list_vars():
    if var.name=="relu_3.tmp_0":
        print(numpy.array(var))

Traceback (most recent call last):
  File "tools/static_trainer.py", line 321, in <module>
    main(args)
  File "tools/static_trainer.py", line 175, in main    
    config, use_visual, log_visual, step_num)
  File "tools/static_trainer.py", line 309, in dataloader_train
    print(numpy.array(paddle.fluid.global_scope().find_var("relu_3.tmp_0").get_tensor()))
AttributeError: 'NoneType' object has no attribute 'get_tensor'

prog = paddle.static.default_main_program()
for var in prog.list_vars():
if var.name=="relu_3.tmp_0":
       paddle.static.Print(var,summarize=-1)
       break

Variable: relu_3.tmp_0
  - lod: {}
  - place: Place(gpu:0)
  - shape: [8, 256]
  - layout: NCHW
  - dtype: float
  - data: [0.591841 0 0 0 0 0.422471 0 0 0 0 0 0.577771 0 0.399299 0 0 0 0 0 0 0 0 0 0 0 0 0 0.644693 0 0 0 0 0 0 0 0 0.243837 0 0.53221 0.503004 0 0 0 0 0.546784 
0 0 0 0 0 0 0 0 0 0 0 0 0 0.446295 0 0 0 0 0 0 0 0 0.425638 0.593102 0.573454 0 0 0 0 0 0 0 0 0 0 0.384188 0 0 0 0 0.476036 0 0 0 0 0 0 0.475764 0.676034 0 0 0 0 0 0 0 0.346013 0 0 0 0 0.670505 0 0 0 0 0.388909 0 0 0 0 0 0 0 0 0 0.552485 0 0 0 0.438703 0 0 0.532311 0 0 0 0 0 0.603588 0 0 0 0 0.498062 0 0 0 0.595748 0.202045 
0 0 0 0 0 0.274415 0 0 0 0 0 0 0 0 0.524153 0 0 0 0 0 0.374015 0 0.578514 0 0 0.0918211 0 0 0.556775 0.524173 0.602912 0 0 0 0 0 0.622055 0 0 0 0 0 0.454071 0 0 0 
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