提交 cccc61c0 编写于 作者: T tangwei12

fix ctr-dnn local training

上级 afec7a49
...@@ -34,7 +34,7 @@ train: ...@@ -34,7 +34,7 @@ train:
reader: reader:
mode: "dataset" mode: "dataset"
batch_size: 32 batch_size: 2
pipe_command: "python /paddle/eleps/models/ctr_dnn/dataset.py" pipe_command: "python /paddle/eleps/models/ctr_dnn/dataset.py"
train_data_path: "/paddle/eleps/models/ctr_dnn/data/train" train_data_path: "/paddle/eleps/models/ctr_dnn/data/train"
...@@ -45,10 +45,7 @@ train: ...@@ -45,10 +45,7 @@ train:
sparse_feature_number: 1000001 sparse_feature_number: 1000001
sparse_feature_dim: 8 sparse_feature_dim: 8
dense_input_dim: 13 dense_input_dim: 13
fc_sizes: [101, 512, 32] fc_sizes: [512, 256, 128, 32]
# - 1024
# - 512
# - 32
learning_rate: 0.001 learning_rate: 0.001
save: save:
......
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\ No newline at end of file
...@@ -11,6 +11,8 @@ ...@@ -11,6 +11,8 @@
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and # See the License for the specific language governing permissions and
# limitations under the License. # limitations under the License.
from __future__ import print_function
import sys
import paddle.fluid.incubate.data_generator as dg import paddle.fluid.incubate.data_generator as dg
...@@ -37,6 +39,7 @@ class CriteoDataset(dg.MultiSlotDataGenerator): ...@@ -37,6 +39,7 @@ class CriteoDataset(dg.MultiSlotDataGenerator):
This function needs to be implemented by the user, based on data format This function needs to be implemented by the user, based on data format
""" """
features = line.rstrip('\n').split('\t') features = line.rstrip('\n').split('\t')
dense_feature = [] dense_feature = []
sparse_feature = [] sparse_feature = []
for idx in continuous_range_: for idx in continuous_range_:
...@@ -46,6 +49,7 @@ class CriteoDataset(dg.MultiSlotDataGenerator): ...@@ -46,6 +49,7 @@ class CriteoDataset(dg.MultiSlotDataGenerator):
dense_feature.append( dense_feature.append(
(float(features[idx]) - cont_min_[idx - 1]) / (float(features[idx]) - cont_min_[idx - 1]) /
cont_diff_[idx - 1]) cont_diff_[idx - 1])
for idx in categorical_range_: for idx in categorical_range_:
sparse_feature.append( sparse_feature.append(
[hash(str(idx) + features[idx]) % hash_dim_]) [hash(str(idx) + features[idx]) % hash_dim_])
......
...@@ -39,7 +39,7 @@ class Train(object): ...@@ -39,7 +39,7 @@ class Train(object):
fluid.layers.data(name="C" + str(i), fluid.layers.data(name="C" + str(i),
shape=[1], shape=[1],
lod_level=1, lod_level=1,
dtype="int64") for i in range(ids) dtype="int64") for i in range(1, ids)
] ]
return sparse_input_ids, [var.name for var in sparse_input_ids] return sparse_input_ids, [var.name for var in sparse_input_ids]
...@@ -60,7 +60,7 @@ class Train(object): ...@@ -60,7 +60,7 @@ class Train(object):
self.label_input, self.label_input_varname = label_input() self.label_input, self.label_input_varname = label_input()
def input_vars(self): def input_vars(self):
return self.sparse_inputs + [self.dense_input] + [self.label_input] return [self.dense_input] + self.sparse_inputs + [self.label_input]
def input_varnames(self): def input_varnames(self):
return [input.name for input in self.input_vars()] return [input.name for input in self.input_vars()]
......
...@@ -169,7 +169,7 @@ class SingleTrainerWithDataset(SingleTrainer): ...@@ -169,7 +169,7 @@ class SingleTrainerWithDataset(SingleTrainer):
dataset=dataset, dataset=dataset,
fetch_list=self.metrics, fetch_list=self.metrics,
fetch_info=["auc ", "batch auc"], fetch_info=["auc ", "batch auc"],
print_period=100) print_period=1)
context['status'] = 'infer_pass' context['status'] = 'infer_pass'
......
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