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提交 4ff282b0 编写于 作者: T tangwei12
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bug fix

上级 0da6629b
隐藏空白更改
内联 并排
Showing with 6 addition and 6 deletion
fluid/PaddleRec/ctr/network_conf.py
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...@@ -95,11 +95,11 @@ def ctr_deepfm_model(factor_size, sparse_feature_dim, dense_feature_dim, sparse_ ...@@ -95,11 +95,11 @@ def ctr_deepfm_model(factor_size, sparse_feature_dim, dense_feature_dim, sparse_
act="softmax", act="softmax",
param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(fc3.shape[1])))) param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(scale=1 / math.sqrt(fc3.shape[1]))))
cost = fluid.layers.cross_entropy(input=predict, label=words[-1:]) cost = fluid.layers.cross_entropy(input=predict, label=words[-1])
avg_cost = fluid.layers.reduce_sum(cost) avg_cost = fluid.layers.reduce_sum(cost)
accuracy = fluid.layers.accuracy(input=predict, label=words[-1:]) accuracy = fluid.layers.accuracy(input=predict, label=words[-1])
auc_var, batch_auc_var, auc_states = \ auc_var, batch_auc_var, auc_states = \
fluid.layers.auc(input=predict, label=words[-1:], num_thresholds=2 ** 12, slide_steps=20) fluid.layers.auc(input=predict, label=words[-1], num_thresholds=2 ** 12, slide_steps=20)
return avg_cost, auc_var, batch_auc_var, py_reader return avg_cost, auc_var, batch_auc_var, py_reader
...@@ -150,10 +150,10 @@ def ctr_dnn_model(embedding_size, sparse_feature_dim): ...@@ -150,10 +150,10 @@ def ctr_dnn_model(embedding_size, sparse_feature_dim):
param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal( param_attr=fluid.ParamAttr(initializer=fluid.initializer.Normal(
scale=1 / math.sqrt(fc3.shape[1])))) scale=1 / math.sqrt(fc3.shape[1]))))
cost = fluid.layers.cross_entropy(input=predict, label=words[-1:]) cost = fluid.layers.cross_entropy(input=predict, label=words[-1])
avg_cost = fluid.layers.reduce_sum(cost) avg_cost = fluid.layers.reduce_sum(cost)
accuracy = fluid.layers.accuracy(input=predict, label=words[-1:]) accuracy = fluid.layers.accuracy(input=predict, label=words[-1])
auc_var, batch_auc_var, auc_states = \ auc_var, batch_auc_var, auc_states = \
fluid.layers.auc(input=predict, label=words[-1:], num_thresholds=2 ** 12, slide_steps=20) fluid.layers.auc(input=predict, label=words[-1], num_thresholds=2 ** 12, slide_steps=20)
return avg_cost, auc_var, batch_auc_var, py_reader return avg_cost, auc_var, batch_auc_var, py_reader
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