提交 020f1f78 编写于 作者: P peterzhang2029

rename the model config file

上级 672e8565
...@@ -2,7 +2,7 @@ import click ...@@ -2,7 +2,7 @@ import click
import gzip import gzip
import paddle.v2 as paddle import paddle.v2 as paddle
from model import Model from network_conf import Model
from reader import DataGenerator from reader import DataGenerator
from decoder import ctc_greedy_decoder from decoder import ctc_greedy_decoder
from utils import get_file_list, load_dict, load_reverse_dict from utils import get_file_list, load_dict, load_reverse_dict
......
...@@ -13,7 +13,8 @@ class Model(object): ...@@ -13,7 +13,8 @@ class Model(object):
:type num_classes: int :type num_classes: int
:param shape: The size of the input images. :param shape: The size of the input images.
:type shape: tuple of 2 int :type shape: tuple of 2 int
:param is_infer: For inference or not :param is_infer: The boolean parameter indicating
inferring or training.
:type shape: bool :type shape: bool
''' '''
self.num_classes = num_classes self.num_classes = num_classes
...@@ -90,11 +91,13 @@ class Model(object): ...@@ -90,11 +91,13 @@ class Model(object):
def conv_groups(self, input, num, with_bn): def conv_groups(self, input, num, with_bn):
''' '''
Get the image features with image convolution group.
:param input: Input layer. :param input: Input layer.
:type input: LayerOutput :type input: LayerOutput
:param num: Number of the filters. :param num: Number of the filters.
:type num: int :type num: int
:param with_bn: Whether with batch normalization. :param with_bn: Use batch normalization or not.
:type with_bn: bool :type with_bn: bool
''' '''
assert num % 4 == 0 assert num % 4 == 0
......
...@@ -4,7 +4,7 @@ import click ...@@ -4,7 +4,7 @@ import click
import paddle.v2 as paddle import paddle.v2 as paddle
from config import TrainerConfig as conf from config import TrainerConfig as conf
from model import Model from network_conf import Model
from reader import DataGenerator from reader import DataGenerator
from utils import get_file_list, build_label_dict, load_dict from utils import get_file_list, build_label_dict, load_dict
......
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