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Commit dc2af579 authored by anivegesana's avatar anivegesana
Browse files

Remove _use_bias parameter in DarkConv

parent e0ada7c6
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Showing with 8 additions and 23 deletions
official/vision/beta/projects/yolo/modeling/layers/nn_blocks.py
View file @ dc2af579
......@@ -29,7 +29,6 @@ class ConvBN(tf.keras.layers.Layer):
padding: string 'valid' or 'same', if same, then pad the image, else do not
dialtion_rate: tuple to indicate how much to modulate kernel weights and
how many pixels in a feature map to skip
use_bias: boolean to indicate whether to use bias in convolution layer
kernel_initializer: string to indicate which function to use to initialize weights
bias_initializer: string to indicate which function to use to initialize bias
kernel_regularizer: string to indicate which function to use to regularizer weights
......@@ -51,7 +50,6 @@ class ConvBN(tf.keras.layers.Layer):
strides=(1, 1),
padding='same',
dilation_rate=(1, 1),
use_bias=True,
kernel_initializer='glorot_uniform',
bias_initializer='zeros',
bias_regularizer=None,
......@@ -70,7 +68,6 @@ class ConvBN(tf.keras.layers.Layer):
self._strides = strides
self._padding = padding
self._dilation_rate = dilation_rate
self._use_bias = use_bias
self._kernel_initializer = kernel_initializer
self._bias_initializer = bias_initializer
self._kernel_regularizer = kernel_regularizer
......@@ -78,8 +75,6 @@ class ConvBN(tf.keras.layers.Layer):
# batch normalization params
self._use_bn = use_bn
if self._use_bn:
self._use_bias = False
self._use_sync_bn = use_sync_bn
self._norm_moment = norm_momentum
self._norm_epsilon = norm_epsilon
......@@ -107,13 +102,15 @@ class ConvBN(tf.keras.layers.Layer):
else:
self._zeropad = Identity()
use_bias = not self._use_bn
self.conv = tf.keras.layers.Conv2D(
filters=self._filters,
kernel_size=self._kernel_size,
strides=self._strides,
padding="valid",
dilation_rate=self._dilation_rate,
use_bias=self._use_bias,
use_bias=use_bias,
kernel_initializer=self._kernel_initializer,
bias_initializer=self._bias_initializer,
kernel_regularizer=self._kernel_regularizer,
......@@ -157,7 +154,6 @@ class ConvBN(tf.keras.layers.Layer):
"strides": self._strides,
"padding": self._padding,
"dilation_rate": self._dilation_rate,
"use_bias": self._use_bias,
"kernel_initializer": self._kernel_initializer,
"bias_initializer": self._bias_initializer,
"bias_regularizer": self._bias_regularizer,
......@@ -183,7 +179,6 @@ class DarkResidual(tf.keras.layers.Layer):
Args:
filters: integer for output depth, or the number of features to learn
use_bias: boolean to indicate whether to use bias in convolution layer
kernel_initializer: string to indicate which function to use to initialize weights
bias_initializer: string to indicate which function to use to initialize bias
kernel_regularizer: string to indicate which function to use to regularizer weights
......@@ -205,7 +200,6 @@ class DarkResidual(tf.keras.layers.Layer):
def __init__(self,
filters=1,
filter_scale=2,
use_bias=True,
kernel_initializer='glorot_uniform',
bias_initializer='zeros',
kernel_regularizer=None,
......@@ -226,7 +220,6 @@ class DarkResidual(tf.keras.layers.Layer):
# ConvBN params
self._filters = filters
self._filter_scale = filter_scale
self._use_bias = use_bias
self._kernel_initializer = kernel_initializer
self._bias_initializer = bias_initializer
self._bias_regularizer = bias_regularizer
......@@ -247,7 +240,6 @@ class DarkResidual(tf.keras.layers.Layer):
def build(self, input_shape):
_dark_conv_args = {
"use_bias": self._use_bias,
"kernel_initializer": self._kernel_initializer,
"bias_initializer": self._bias_initializer,
"bias_regularizer": self._bias_regularizer,
......@@ -302,7 +294,6 @@ class DarkResidual(tf.keras.layers.Layer):
# used to store/share parameters to reconstruct the model
layer_config = {
"filters": self._filters,
"use_bias": self._use_bias,
"kernel_initializer": self._kernel_initializer,
"bias_initializer": self._bias_initializer,
"kernel_regularizer": self._kernel_regularizer,
......@@ -331,7 +322,6 @@ class CSPTiny(tf.keras.layers.Layer):
Args:
filters: integer for output depth, or the number of features to learn
use_bias: boolean to indicate whether to use bias in convolution layer
kernel_initializer: string to indicate which function to use to initialize weights
bias_initializer: string to indicate which function to use to initialize bias
use_bn: boolean for whether to use batch normalization
......@@ -353,7 +343,6 @@ class CSPTiny(tf.keras.layers.Layer):
"""
def __init__(self,
filters=1,
use_bias=True,
kernel_initializer='glorot_uniform',
bias_initializer='zeros',
bias_regularizer=None,
......@@ -371,7 +360,6 @@ class CSPTiny(tf.keras.layers.Layer):
# ConvBN params
self._filters = filters
self._use_bias = use_bias
self._kernel_initializer = kernel_initializer
self._bias_initializer = bias_initializer
self._bias_regularizer = bias_regularizer
......@@ -394,7 +382,6 @@ class CSPTiny(tf.keras.layers.Layer):
def build(self, input_shape):
_dark_conv_args = {
"use_bias": self._use_bias,
"kernel_initializer": self._kernel_initializer,
"bias_initializer": self._bias_initializer,
"bias_regularizer": self._bias_regularizer,
......@@ -416,7 +403,6 @@ class CSPTiny(tf.keras.layers.Layer):
kernel_size=(3, 3),
strides=(1, 1),
padding='same',
use_bias=self._use_bias,
kernel_initializer=self._kernel_initializer,
bias_initializer=self._bias_initializer,
bias_regularizer=self._bias_regularizer,
......@@ -463,7 +449,6 @@ class CSPTiny(tf.keras.layers.Layer):
# used to store/share parameters to reconsturct the model
layer_config = {
"filters": self._filters,
"use_bias": self._use_bias,
"strides": self._strides,
"kernel_initializer": self._kernel_initializer,
"bias_initializer": self._bias_initializer,
......
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