masahi commented on a change in pull request #4936: [Tutorial] Add a tutorial for PyTorch URL: https://github.com/apache/incubator-tvm/pull/4936#discussion_r384194277
########## File path: tutorials/frontend/from_pytorch.py ########## @@ -0,0 +1,168 @@ +# 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 +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. +""" +Compile PyTorch Models +====================== +**Author**: `Alex Wong <https://github.com/alexwong/>`_ + +This article is an introductory tutorial to deploy PyTorch models with Relay. + +For us to begin with, PyTorch should be installed. +TorchVision is also required since we will be using it as our model zoo. + +A quick solution is to install via pip + +.. code-block:: bash + + pip install torch==1.4.0 + pip install torchvision==0.5.0 + +or please refer to official site +https://pytorch.org/get-started/locally/ + +PyTorch versions should be backwards compatible but should be used +with the proper TorchVision version. + +Currently, TVM supports PyTorch 1.4, 1.3, and 1.2. Other versions may +be unstable. +""" + +# tvm, relay +import tvm +from tvm import relay + +# numpy, packaging +import numpy as np +from packaging import version +from tvm.contrib.download import download_testdata + +# PyTorch imports +import torch +import torchvision + +###################################################################### +# Load a pretrained PyTorch model +# ------------------------------- +model_name = 'resnet18' +model = getattr(torchvision.models, model_name)(pretrained=True) +model = model.float().eval() + +# We grab the TorchScripted model via tracing +input_shape = [1, 3, 224, 224] +input_data = torch.randn(input_shape).float() +scripted_model = torch.jit.trace(model, input_data).float().eval() + +###################################################################### +# Load a test image +# ----------------- +# Classic cat example! +from PIL import Image +img_url = 'https://raw.githubusercontent.com/Cadene/pretrained-models.pytorch/master/data/cat_224.jpg' +img_path = download_testdata(img_url, 'cat_224.png', module='data') +img = Image.open(img_path) + +# Preprocess the image and convert to tensor +from torchvision import transforms +my_preprocess = transforms.Compose([ + transforms.Resize(256), + transforms.CenterCrop(224), + transforms.ToTensor(), + transforms.Normalize(mean=[0.485, 0.456, 0.406], + std=[0.229, 0.224, 0.225]) +]) +img = my_preprocess(img) +img = np.expand_dims(img, 0) + +###################################################################### +# Import the graph to Relay +# ------------------------- +# Convert PyTorch graph to Relay graph. +shape_dict = {'input0': img.shape} +mod, params = relay.frontend.from_pytorch(scripted_model, + shape_dict) + +###################################################################### +# Relay Build +# ----------- +# Compile the graph to llvm target with given input specification. +target = 'llvm' +target_host = 'llvm' +layout = None Review comment: Remove layout ---------------------------------------------------------------- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. For queries about this service, please contact Infrastructure at: us...@infra.apache.org With regards, Apache Git Services
