jganzabal

This configuration worked for me, hope it helps

It is based on: https://becominghuman.ai/deep-learning-gaming-build-with-nvidia-titan-xp-and-macbook-pro-with-thunderbolt2-5ceee7167f8b

and on: https://stackoverflow.com/questions/44744737/tensorflow-mac-os-gpu-support

Hardware

ndronen

#!/usr/bin/env python
"""
A quick, partial implementation of ENet (https://arxiv.org/abs/1606.02147) using PyTorch.
The original Torch ENet implementation can process a 480x360 image in ~12 ms (on a P2 AWS
instance).  TensorFlow takes ~35 ms.  The PyTorch implementation takes ~25 ms, an improvement
over TensorFlow, but worse than the original Torch.
"""

from __future__ import absolute_import

jfsantos

'''
A logistic regression example using the meta-graph checkpointing
features of Tensorflow.

Author: João Felipe Santos, based on code by Aymeric Damien
(https://github.com/aymericdamien/TensorFlow-Examples/)
'''

from __future__ import print_function

sklam

"""
Demonstrating CUDA JIT integration
"""
from __future__ import print_function
from numba import cuda
import numpy
import os

# Declare function to link to
bar = cuda.declare_device('bar', 'int32(voidptr, int32)')

sklam

# GL interoperability example, by Peter Berrington.
# Draws a rotating teapot, using cuda to invert the RGB value
# each frame

from OpenGL.GL import *
from OpenGL.GLUT import *
from OpenGL.GLU import *
from OpenGL.GL.ARB.vertex_buffer_object import *
from OpenGL.GL.ARB.pixel_buffer_object import *

harpone

import tensorflow as tf
from tensorflow.python.framework import ops
import numpy as np

# Define custom py_func which takes also a grad op as argument:
def py_func(func, inp, Tout, stateful=True, name=None, grad=None):
    
    # Need to generate a unique name to avoid duplicates:
    rnd_name = 'PyFuncGrad' + str(np.random.randint(0, 1E+8))
    

udibr

import numpy as np
from keras.layers import GRU, initializations, K
from collections import OrderedDict

class GRULN(GRU):
    '''Gated Recurrent Unit with Layer Normalization
    Current impelemtation only works with consume_less = 'gpu' which is already
    set.

    # Arguments

joelouismarino

from __future__ import print_function
import imageio
from PIL import Image
import numpy as np
import keras

from keras.layers import Input, Dense, Conv2D, MaxPooling2D, AveragePooling2D, ZeroPadding2D, Dropout, Flatten, Concatenate, Reshape, Activation
from keras.models import Model
from keras.regularizers import l2
from keras.optimizers import SGD

ntasfi

""" Interface with the PLE environment

Authors: Vincent Francois-Lavet, David Taralla
Modified by: Norman Tasfi
"""
import numpy as np
import cv2
from ple import PLE

from deeprl.base_classes import Environment

albertomontesg