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Commit a5d7a452 authored by Scott Zhu's avatar Scott Zhu Committed by A. Unique TensorFlower
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Prepare for upcoming keras initializer change. 

PiperOrigin-RevId: 451476877
parent 6b6b3a9c
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Showing with 35 additions and 18 deletions
official/projects/s3d/modeling/inception_utils.py
View file @ a5d7a452
......@@ -17,6 +17,7 @@ from typing import Callable, Dict, Optional, Sequence, Set, Text, Tuple, Type, U
import tensorflow as tf
from official.modeling import tf_utils
from official.projects.s3d.modeling import net_utils
from official.vision.modeling.layers import nn_blocks_3d
......@@ -126,7 +127,7 @@ def inception_v1_stem_cells(
strides=[2, 2, 2],
padding='same',
use_bias=False,
kernel_initializer=kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(kernel_initializer),
kernel_regularizer=kernel_regularizer,
name=layer_naming_fn(end_point))(
inputs)
......@@ -161,7 +162,7 @@ def inception_v1_stem_cells(
kernel_size=[1, 1, 1],
padding='same',
use_bias=False,
kernel_initializer=kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(kernel_initializer),
kernel_regularizer=kernel_regularizer,
name=layer_naming_fn(end_point))(
net)
......@@ -191,7 +192,7 @@ def inception_v1_stem_cells(
norm_momentum=norm_momentum,
norm_epsilon=norm_epsilon,
temporal_conv_initializer=temporal_conv_initializer,
kernel_initializer=kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(kernel_initializer),
kernel_regularizer=kernel_regularizer,
name=layer_naming_fn(end_point))(
net)
......@@ -330,7 +331,8 @@ class InceptionV1CellLayer(tf.keras.layers.Layer):
kernel_size=[1, 1, 1],
padding='same',
use_bias=False,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
kernel_regularizer=self._kernel_regularizer),
# norm
dict(
......@@ -349,7 +351,8 @@ class InceptionV1CellLayer(tf.keras.layers.Layer):
kernel_size=[1, 1, 1],
padding='same',
use_bias=False,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
kernel_regularizer=self._kernel_regularizer),
# norm
dict(
......@@ -371,7 +374,8 @@ class InceptionV1CellLayer(tf.keras.layers.Layer):
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
temporal_conv_initializer=self._temporal_conv_initializer,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
kernel_regularizer=self._kernel_regularizer),
]
branch_2_params = [
......@@ -381,7 +385,8 @@ class InceptionV1CellLayer(tf.keras.layers.Layer):
kernel_size=[1, 1, 1],
padding='same',
use_bias=False,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
kernel_regularizer=self._kernel_regularizer),
# norm
dict(
......@@ -403,7 +408,8 @@ class InceptionV1CellLayer(tf.keras.layers.Layer):
norm_momentum=self._norm_momentum,
norm_epsilon=self._norm_epsilon,
temporal_conv_initializer=self._temporal_conv_initializer,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
kernel_regularizer=self._kernel_regularizer)
]
branch_3_params = [
......@@ -413,7 +419,8 @@ class InceptionV1CellLayer(tf.keras.layers.Layer):
kernel_size=[1, 1, 1],
padding='same',
use_bias=False,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
kernel_regularizer=self._kernel_regularizer),
# norm
dict(
......
official/projects/s3d/modeling/net_utils.py
View file @ a5d7a452
......@@ -16,6 +16,7 @@
from typing import Any, Text, Sequence, Union
import tensorflow as tf
from official.modeling import tf_utils
WEIGHT_INITIALIZER = {
'Xavier': tf.keras.initializers.GlorotUniform,
......@@ -94,7 +95,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[self._kernel_size] * 3,
strides=self._strides,
dilation_rate=self._rates,
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
elif self._conv_type == '2d':
conv_layer_params.append(
......@@ -103,7 +105,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[1, self._kernel_size, self._kernel_size],
strides=[1, self._strides[1], self._strides[2]],
dilation_rate=[1, self._rates[1], self._rates[2]],
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
elif self._conv_type == '1+2d':
channels_in = input_shape[self._channel_axis]
......@@ -113,7 +116,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[self._kernel_size, 1, 1],
strides=[self._strides[0], 1, 1],
dilation_rate=[self._rates[0], 1, 1],
kernel_initializer=self._temporal_conv_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._temporal_conv_initializer),
))
conv_layer_params.append(
dict(
......@@ -121,7 +125,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[1, self._kernel_size, self._kernel_size],
strides=[1, self._strides[1], self._strides[2]],
dilation_rate=[1, self._rates[1], self._rates[2]],
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
elif self._conv_type == '2+1d':
conv_layer_params.append(
......@@ -130,7 +135,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[1, self._kernel_size, self._kernel_size],
strides=[1, self._strides[1], self._strides[2]],
dilation_rate=[1, self._rates[1], self._rates[2]],
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
conv_layer_params.append(
dict(
......@@ -138,7 +144,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[self._kernel_size, 1, 1],
strides=[self._strides[0], 1, 1],
dilation_rate=[self._rates[0], 1, 1],
kernel_initializer=self._temporal_conv_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._temporal_conv_initializer),
))
elif self._conv_type == '1+1+1d':
conv_layer_params.append(
......@@ -147,7 +154,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[1, 1, self._kernel_size],
strides=[1, 1, self._strides[2]],
dilation_rate=[1, 1, self._rates[2]],
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
conv_layer_params.append(
dict(
......@@ -155,7 +163,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[1, self._kernel_size, 1],
strides=[1, self._strides[1], 1],
dilation_rate=[1, self._rates[1], 1],
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
conv_layer_params.append(
dict(
......@@ -163,7 +172,8 @@ class ParameterizedConvLayer(tf.keras.layers.Layer):
kernel_size=[self._kernel_size, 1, 1],
strides=[self._strides[0], 1, 1],
dilation_rate=[self._rates[0], 1, 1],
kernel_initializer=self._kernel_initializer,
kernel_initializer=tf_utils.clone_initializer(
self._kernel_initializer),
))
else:
raise ValueError('Unsupported conv_type: {}'.format(self._conv_type))
......
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