Skip to content

[refactor] delete network_builder func #81

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 1 commit into
base: master
Choose a base branch
from
Open

[refactor] delete network_builder func #81

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
18 changes: 8 additions & 10 deletions nets/deep_sort/residual_net.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -10,9 +10,10 @@ def _batch_norm_fn(x, scope=None):


def create_link(
incoming, network_builder, scope, nonlinearity=tf.nn.elu,
incoming, scope, nonlinearity=tf.nn.elu,
weights_initializer=tf.truncated_normal_initializer(stddev=1e-3),
regularizer=None, is_first=False, summarize_activations=True):
i_block_bias_initializer, i_block_increase_dim, regularizer=None,
is_first=False, summarize_activations=True):
if is_first:
network = incoming
else:
Expand All @@ -22,8 +23,9 @@ def create_link(
tf.summary.histogram(scope+"/activations", network)

pre_block_network = incoming
post_block_network = network_builder(network, scope)

post_block_network = create_inner_block(
network, scope, nonlinearity, weights_initializer, i_block_bias_initializer,
regularizer, i_block_increase_dim, summarize_activations)
incoming_dim = pre_block_network.get_shape().as_list()[-1]
outgoing_dim = post_block_network.get_shape().as_list()[-1]
if incoming_dim != outgoing_dim:
Expand Down Expand Up @@ -74,11 +76,7 @@ def residual_block(incoming, scope, nonlinearity=tf.nn.elu,
increase_dim=False, is_first=False,
summarize_activations=True):

def network_builder(x, s):
return create_inner_block(
x, s, nonlinearity, weights_initializer, bias_initializer,
regularizer, increase_dim, summarize_activations)

return create_link(
incoming, network_builder, scope, nonlinearity, weights_initializer,
incoming, scope, nonlinearity, weights_initializer,
bias_initializer, increase_dim,
regularizer, is_first, summarize_activations)