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Migration to Tensorflow2 #144

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Migration to Tensorflow2 #144

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17f3722
Automatic conversion via tf_upgrade_v2.
woj-i Aug 28, 2020
8addf9c
Tf1 -> Tf2: LayerNormBasicLSTMCell to tfa.rnn.LayerNormLSTMCell
woj-i Aug 28, 2020
1032bc1
Tf1 -> Tf2: layer_norm to tf.keras.layers, LuongAttention
woj-i Aug 28, 2020
d591bea
Tf1 -> Tf2: migrate tf.contrib
woj-i Aug 29, 2020
640fb55
Tf1 -> Tf2: LSTMCell
woj-i Sep 27, 2020
57efd45
Tf1 -> Tf2: MLDG
woj-i Sep 27, 2020
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Tf1 -> Tf2: layer_norm to tf.keras.layers, LuongAttention
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@woj-i
woj-i committed Aug 28, 2020
commit 1032bc1085f8322de4ab7bca5649b972937ba595
2 changes: 1 addition & 1 deletion btgym/algorithms/nn/ae.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
import numpy as np
import tensorflow as tf
from tensorflow.contrib.layers import flatten as batch_flatten
from tensorflow.contrib.layers import layer_norm as norm_layer

from btgym.algorithms.nn.layers import normalized_columns_initializer, linear, conv2d

Expand Down Expand Up @@ -35,6 +34,7 @@ def conv2d_encoder(x,
layer_shapes = [x.get_shape()]
layer_outputs = []
for i, layer_spec in enumerate(layer_config, 1):
norm_layer = tf.keras.layers.LayerNormalization()
x = tf.nn.elu(
norm_layer(
conv2d(
Expand Down
2 changes: 1 addition & 1 deletion btgym/algorithms/nn/networks.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,6 @@
import numpy as np
import tensorflow as tf
import tensorflow.contrib.rnn as rnn
from tensorflow.contrib.layers import layer_norm as norm_layer
from tensorflow.python.util.nest import flatten as flatten_nested

from btgym.algorithms.nn.layers import normalized_columns_initializer, categorical_sample
Expand Down Expand Up @@ -38,6 +37,7 @@ def conv_2d_network(x,
"""
with tf.compat.v1.variable_scope(name, reuse=reuse):
for i, num_filters in enumerate(conv_2d_num_filters):
norm_layer = tf.keras.layers.LayerNormalization()
x = tf.nn.elu(
norm_layer(
conv_2d_layer_ref(
Expand Down
9 changes: 5 additions & 4 deletions btgym/research/casual_conv/networks.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@

import tensorflow as tf
from tensorflow.contrib.layers import layer_norm as norm_layer
import tensorflow_addons as tfa

import numpy as np
import math
Expand Down Expand Up @@ -78,7 +78,8 @@ def conv_1d_casual_encoder(
# b2t:
y = tf.reshape(y, [-1, num_time_batches, conv_1d_num_filters], name='layer_{}_output'.format(i))

y = norm_layer(y)
normalization_layer = tf.keras.layers.LayerNormalization()
y = normalization_layer(y)
if conv_1d_activation is not None:
y = conv_1d_activation(y)

Expand Down Expand Up @@ -137,7 +138,7 @@ def conv_1d_casual_encoder(
return encoded


def attention_layer(inputs, attention_ref=tf.contrib.seq2seq.LuongAttention, name='attention_layer', **kwargs):
def attention_layer(inputs, attention_ref=tfa.seq2seq.LuongAttention, name='attention_layer', **kwargs):
"""
Temporal attention layer.
Computes attention context based on last(left) value in time dim.
Expand Down Expand Up @@ -201,7 +202,7 @@ def conv_1d_casual_attention_encoder(
conv_1d_num_filters=32,
conv_1d_filter_size=2,
conv_1d_activation=tf.nn.elu,
conv_1d_attention_ref=tf.contrib.seq2seq.LuongAttention,
conv_1d_attention_ref=tfa.seq2seq.LuongAttention,
name='casual_encoder',
keep_prob=None,
conv_1d_gated=False,
Expand Down
2 changes: 1 addition & 1 deletion btgym/research/encoder_test/networks.py
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Original file line number Diff line number Diff line change
@@ -1,7 +1,6 @@
import numpy as np
import tensorflow as tf
import tensorflow.contrib.rnn as rnn
from tensorflow.contrib.layers import layer_norm as norm_layer
from tensorflow.python.util.nest import flatten as flatten_nested

from btgym.algorithms.nn.layers import normalized_columns_initializer, categorical_sample
Expand Down Expand Up @@ -35,6 +34,7 @@ def conv_2d_network_skip(x,
layers = []
with tf.compat.v1.variable_scope(name, reuse=reuse):
for i, num_filters in enumerate(conv_2d_num_filters):
norm_layer = tf.keras.layers.LayerNormalization()
x = tf.nn.elu(
norm_layer(
conv_2d_layer_ref(
Expand Down