From 63993d46e5cd80087ab8291a740e5158dd5786fc Mon Sep 17 00:00:00 2001
From: Amir MOHAMMADI <amir.mohammadi@idiap.ch>
Date: Fri, 7 Feb 2020 16:08:16 +0100
Subject: [PATCH] nitpick
---
bob/learn/tensorflow/models/mcae.py | 11 ++---------
1 file changed, 2 insertions(+), 9 deletions(-)
diff --git a/bob/learn/tensorflow/models/mcae.py b/bob/learn/tensorflow/models/mcae.py
index e3e565fa..07cbb529 100644
--- a/bob/learn/tensorflow/models/mcae.py
+++ b/bob/learn/tensorflow/models/mcae.py
@@ -32,11 +32,8 @@ class ConvEncoder(tf.keras.Model):
l2_kw = get_l2_kw(weight_decay)
layers = []
for i, (filters, kernel_size, strides, padding) in enumerate(encoder_layers):
- pad_kw = {}
- # if i == 0:
- # pad_kw["input_shape"] = input_shape
pad = tf.keras.layers.ZeroPadding2D(
- padding=padding, data_format=data_format, name=f"pad_{i}", **pad_kw
+ padding=padding, data_format=data_format, name=f"pad_{i}"
)
conv = tf.keras.layers.Conv2D(
filters,
@@ -75,17 +72,13 @@ class ConvDecoder(tf.keras.Model):
l2_kw = get_l2_kw(weight_decay)
layers = []
for i, (filters, kernel_size, strides, cropping) in enumerate(decoder_layers):
- dconv_kw = {}
- dconv_kw.update(l2_kw)
- # if i == 0:
- # dconv_kw["input_shape"] = embedding_shape
dconv = tf.keras.layers.Conv2DTranspose(
filters,
kernel_size,
strides=strides,
data_format=data_format,
name=f"dconv_{i}",
- **dconv_kw,
+ **l2_kw,
)
crop = tf.keras.layers.Cropping2D(
cropping=cropping, data_format=data_format, name=f"crop_{i}"
--
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