From bb967869a6ad2c3919b67b0623ce33e36349d413 Mon Sep 17 00:00:00 2001 From: Vinh Khuc Date: Wed, 16 Sep 2020 02:40:34 -0700 Subject: [PATCH] Remove support for Python 2. Misc fixes. --- .travis.yml | 1 - 1_linear_regression.py | 1 + 2_logistic_regression.py | 2 ++ 3_neural_net.py | 2 ++ 4_modern_neural_net.py | 2 ++ 5_convolutional_net.py | 2 ++ 6_lstm.py | 3 ++- data_util.py | 14 +++----------- 8 files changed, 14 insertions(+), 13 deletions(-) diff --git a/.travis.yml b/.travis.yml index 9b4ecd5..0ac9a5d 100644 --- a/.travis.yml +++ b/.travis.yml @@ -2,7 +2,6 @@ os: - linux language: python python: - - 2.7 - 3.6 cache: bundler install: diff --git a/1_linear_regression.py b/1_linear_regression.py index 4c754ae..a56d4db 100644 --- a/1_linear_regression.py +++ b/1_linear_regression.py @@ -10,6 +10,7 @@ def build_model(): def train(model, loss, optimizer, x, y): + model.train() x = Variable(x, requires_grad=False) y = Variable(y, requires_grad=False) diff --git a/2_logistic_regression.py b/2_logistic_regression.py index 0494090..209dfef 100644 --- a/2_logistic_regression.py +++ b/2_logistic_regression.py @@ -17,6 +17,7 @@ def build_model(input_dim, output_dim): def train(model, loss, optimizer, x_val, y_val): + model.train() x = Variable(x_val, requires_grad=False) y = Variable(y_val, requires_grad=False) @@ -37,6 +38,7 @@ def train(model, loss, optimizer, x_val, y_val): def predict(model, x_val): + model.eval() x = Variable(x_val, requires_grad=False) output = model.forward(x) return output.data.numpy().argmax(axis=1) diff --git a/3_neural_net.py b/3_neural_net.py index b8db316..49facd7 100644 --- a/3_neural_net.py +++ b/3_neural_net.py @@ -16,6 +16,7 @@ def build_model(input_dim, output_dim): def train(model, loss, optimizer, x_val, y_val): + model.train() x = Variable(x_val, requires_grad=False) y = Variable(y_val, requires_grad=False) @@ -36,6 +37,7 @@ def train(model, loss, optimizer, x_val, y_val): def predict(model, x_val): + model.eval() x = Variable(x_val, requires_grad=False) output = model.forward(x) return output.data.numpy().argmax(axis=1) diff --git a/4_modern_neural_net.py b/4_modern_neural_net.py index 84f970e..78dbd1f 100644 --- a/4_modern_neural_net.py +++ b/4_modern_neural_net.py @@ -20,6 +20,7 @@ def build_model(input_dim, output_dim): def train(model, loss, optimizer, x_val, y_val): + model.train() x = Variable(x_val, requires_grad=False) y = Variable(y_val, requires_grad=False) @@ -40,6 +41,7 @@ def train(model, loss, optimizer, x_val, y_val): def predict(model, x_val): + model.eval() x = Variable(x_val, requires_grad=False) output = model.forward(x) return output.data.numpy().argmax(axis=1) diff --git a/5_convolutional_net.py b/5_convolutional_net.py index d877961..cddf73d 100644 --- a/5_convolutional_net.py +++ b/5_convolutional_net.py @@ -34,6 +34,7 @@ def forward(self, x): def train(model, loss, optimizer, x_val, y_val): + model.train() x = Variable(x_val, requires_grad=False) y = Variable(y_val, requires_grad=False) @@ -54,6 +55,7 @@ def train(model, loss, optimizer, x_val, y_val): def predict(model, x_val): + model.eval() x = Variable(x_val, requires_grad=False) output = model.forward(x) return output.data.numpy().argmax(axis=1) diff --git a/6_lstm.py b/6_lstm.py index 6b9f44e..8ce7278 100644 --- a/6_lstm.py +++ b/6_lstm.py @@ -1,4 +1,3 @@ -from __future__ import division import numpy as np import torch @@ -24,6 +23,7 @@ def forward(self, x): def train(model, loss, optimizer, x_val, y_val): + model.train() x = Variable(x_val, requires_grad=False) y = Variable(y_val, requires_grad=False) @@ -44,6 +44,7 @@ def train(model, loss, optimizer, x_val, y_val): def predict(model, x_val): + model.eval() x = Variable(x_val, requires_grad=False) output = model.forward(x) return output.data.numpy().argmax(axis=1) diff --git a/data_util.py b/data_util.py index 6400fbf..528ccdf 100644 --- a/data_util.py +++ b/data_util.py @@ -1,14 +1,9 @@ import gzip import os +import urllib.request as request from os import path -import numpy as np - -import sys -if sys.version_info.major < 3: - import urllib -else: - import urllib.request as request +import numpy as np DATASET_DIR = 'datasets/' @@ -23,10 +18,7 @@ def download_file(url, local_path): os.makedirs(dir_path) print("Downloading from '%s' ..." % url) - if sys.version_info.major < 3: - urllib.URLopener().retrieve(url, local_path) - else: - request.urlretrieve(url, local_path) + request.urlretrieve(url, local_path) def download_mnist(local_path):