made initial weights higher-variance
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@ -537,7 +537,7 @@
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Okay, let's start by creating a trainable variable of shape (1, 1152, 10, 16, 8) that will hold all the transformation matrices. The first dimension of size 1 will make this array easy to tile. We initialize this variable randomly using a normal distribution with a standard deviation to 0.01."
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"Okay, let's start by creating a trainable variable of shape (1, 1152, 10, 16, 8) that will hold all the transformation matrices. The first dimension of size 1 will make this array easy to tile. We initialize this variable randomly using a normal distribution with a standard deviation to 0.1."
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]
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},
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{
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@ -546,7 +546,7 @@
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"metadata": {},
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"outputs": [],
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"source": [
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"init_sigma = 0.01\n",
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"init_sigma = 0.1\n",
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"\n",
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"W_init = tf.random_normal(\n",
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" shape=(1, caps1_n_caps, caps2_n_caps, caps2_n_dims, caps1_n_dims),\n",
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