sh1doy

import tensorflow as tf


class ConvLSTM(tf.keras.Model):
    def __init__(self, dim_out):
        super(ConvLSTM, self).__init__()
        self.dim_out = dim_out
        self.Wf = tf.keras.layers.Conv2D(dim_out, 5, 1, "same")
        self.Wu = tf.keras.layers.Conv2D(dim_out, 5, 1, "same")
        self.Wi = tf.keras.layers.Conv2D(dim_out, 5, 1, "same")

koshian2

from keras.layers import Conv2D, Activation, BatchNormalization, Add, Input, GlobalAveragePooling2D, Dense
from keras.models import Model
from keras.optimizers import SGD
from keras.datasets import cifar10
from keras.utils import to_categorical
from keras.initializers import he_normal
from keras.preprocessing.image import ImageDataGenerator
from keras.callbacks import Callback, LearningRateScheduler
from keras.regularizers import l2
import numpy as np

DylanModesitt

from keras import backend as K
from keras import regularizers, constraints, initializers, activations
from keras.layers.recurrent import RNN, Layer, _generate_dropout_mask, _generate_dropout_ones
from keras.engine import InputSpec
from keras.legacy import interfaces
import warnings


# Copied from original keras source
def _time_distributed_dense(x, w, b=None, dropout=None,

jadarve

import numpy as np
import OpenEXR as exr
import Imath

def readEXR(filename):
    """Read color + depth data from EXR image file.
    
    Parameters
    ----------
    filename : str

ypandit

[Unit]
Description=X Virtual Frame Buffer Service
After=network.target

[Service]
ExecStart=/usr/bin/Xvfb :99 -screen 0 1024x768x24

[Install]
WantedBy=multi-user.target