我正在为二进制分类问题编写一个自定义度量。 函数已执行,但我有两个问题: -如果测试总是评估为真 -我不能设法显示张量的值来调试它
RETURNS是全局定义的一维数组
def total_winning(y_true, y_pred):
sess = K.get_session()
ze_zum = 0.0
for i in range(len(RETURNS)):
val = K.gather(y_pred,i)
val2 = RETURNS[i]
val = K.print_tensor(val, message='val = ')
#print( str(val.eval(session=sess)))
if (K.greater(val[0], 0.5)) is not None:
print( "Greater")
val3 = val2
else:
print( "Smaller")
val3 = 0
ze_zum = ze_zum + val3
return K.variable(value=ze_zum, dtype='float64' )
我想保持更复杂的测试循环
问题:
我试着调试的东西
InvalidArgumentError (see above for traceback): You must feed a value for placeholder tensor 'dense_1_input' with dtype float and shape [?,30] [[{{node dense_1_input}} = Placeholderdtype=DT_FLOAT, shape=[?,30], _device="/job:localhost/replica:0/task:0/device:GPU:0"]] [[{{node metrics/total_winning/embedding_lookup/_29}} = _Recvclient_terminated=false, recv_device="/job:localhost/replica:0/task:0/device:CPU:0", send_device="/job:localhost/replica:0/task:0/device:GPU:0", send_device_incarnation=1, tensor_name="edge_33_metrics/total_winning/embedding_lookup", tensor_type=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"]]
目前没有回答
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