ThomasDelteil

ThomasDelteil

ThomasDelteil

ThomasDelteil

{
  "nodes": [
    {
      "op": "null", 
      "name": "data", 
      "inputs": []
    }, 
    {
      "op": "null", 
      "name": "resnetv10_conv0_weight", 

ThomasDelteil

ThomasDelteil

ThomasDelteil

ThomasDelteil

# coding: utf-8

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements.  See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership.  The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License.  You may obtain a copy of the License at
#

ThomasDelteil

import mxnet as mx
import gluonnlp as nlp

# Load GloVe word embeddings
glove = nlp.embedding.create('glove', source='glove.6B.50d')

# Compute 'baby' and 'infant' word embeddings
baby_glove, infant_glove = glove['baby'], glove['infant']

# Load pre-trained AWD LSTM language model and get the embedding

ThomasDelteil

import multiprocessing, time
import mxnet as mx
from mxnet import nd, gluon, autograd

# ctx
ctx = mx.gpu()
# data
def transform(x):
    #x = mx.image.resize_short(x, 32)
    x = x.transpose((2, 0, 1))