diff --git a/examples/manual_reporting.py b/examples/manual_reporting.py index 4ef19f13..1da9080d 100644 --- a/examples/manual_reporting.py +++ b/examples/manual_reporting.py @@ -1,5 +1,6 @@ # TRAINS - Example of manual graphs and statistics reporting # +from PIL import Image import numpy as np import logging from trains import Task @@ -49,11 +50,12 @@ logger.report_scatter3d("example_scatter_3d", "series_xyz", iteration=1, scatter # reporting images m = np.eye(256, 256, dtype=np.float) -logger.report_image("test case", "image float", iteration=1, matrix=m) +logger.report_image("test case", "image float", iteration=1, image=m) m = np.eye(256, 256, dtype=np.uint8)*255 -logger.report_image("test case", "image uint8", iteration=1, matrix=m) +logger.report_image("test case", "image uint8", iteration=1, image=m) m = np.concatenate((np.atleast_3d(m), np.zeros((256, 256, 2), dtype=np.uint8)), axis=2) -logger.report_image("test case", "image color red", iteration=1, matrix=m) - +logger.report_image("test case", "image color red", iteration=1, image=m) +image_open = Image.open('./samples/picasso.jpg') +logger.report_image("test case", "image PIL", iteration=1, image=image_open) # flush reports (otherwise it will be flushed in the background, every couple of seconds) logger.flush() diff --git a/examples/pytorch_mnist.py b/examples/pytorch_mnist.py index 81b537ee..f80ffbb3 100644 --- a/examples/pytorch_mnist.py +++ b/examples/pytorch_mnist.py @@ -2,6 +2,9 @@ # from __future__ import print_function import argparse +import os +from tempfile import gettempdir + import torch import torch.nn as nn import torch.nn.functional as F @@ -117,7 +120,7 @@ def main(): test(args, model, device, test_loader) if (args.save_model): - torch.save(model.state_dict(), "/tmp/mnist_cnn.pt") + torch.save(model.state_dict(), os.path.join(gettempdir(), "mnist_cnn.pt")) if __name__ == '__main__': diff --git a/examples/pytorch_tensorboard.py b/examples/pytorch_tensorboard.py index 25343fd4..9a85b168 100644 --- a/examples/pytorch_tensorboard.py +++ b/examples/pytorch_tensorboard.py @@ -3,6 +3,9 @@ from __future__ import print_function import argparse +import os +from tempfile import gettempdir + import torch import torch.nn as nn import torch.nn.functional as F @@ -122,5 +125,5 @@ def test(): for epoch in range(1, args.epochs + 1): train(epoch) - torch.save(model, '/tmp/model{}'.format(epoch)) + torch.save(model, os.path.join(gettempdir(), 'model{}'.format(epoch))) test() diff --git a/examples/pytorch_tensorboardX.py b/examples/pytorch_tensorboardX.py index df783e22..adc01310 100644 --- a/examples/pytorch_tensorboardX.py +++ b/examples/pytorch_tensorboardX.py @@ -3,6 +3,9 @@ from __future__ import print_function import argparse +import os +from tempfile import gettempdir + import torch import torch.nn as nn import torch.nn.functional as F @@ -122,5 +125,5 @@ def test(): for epoch in range(1, args.epochs + 1): train(epoch) - torch.save(model, '/tmp/model{}'.format(epoch)) + torch.save(model, os.path.join(gettempdir(), 'model{}'.format(epoch))) test() diff --git a/examples/requirements.txt b/examples/requirements.txt index c63b5e2c..edea3ff1 100644 --- a/examples/requirements.txt +++ b/examples/requirements.txt @@ -2,7 +2,7 @@ absl-py>=0.7.1 Keras>=2.2.4 joblib>=0.13.2 matplotlib>=3.1.1 ; python_version >= '3.6' -matplotlib == 3.0.3 ; python_version < '3.6' +matplotlib >= 2.2.4 ; python_version < '3.6' seaborn>=0.9.0 sklearn>=0.0 tensorboard>=1.14.0 @@ -10,7 +10,7 @@ tensorboardX>=1.8 tensorflow>=1.14.0 torch>=1.1.0 torchvision>=0.3.0 -xgboost>=0.90 - +xgboost>=0.90 ; python_version >= '3' +xgboost >= 0.82 ; python_version < '3' # sudo apt-get install graphviz graphviz>=0.8 diff --git a/examples/tensorboard_pr_curve.py b/examples/tensorboard_pr_curve.py index 7f153e18..b490fdad 100644 --- a/examples/tensorboard_pr_curve.py +++ b/examples/tensorboard_pr_curve.py @@ -30,6 +30,7 @@ from __future__ import division from __future__ import print_function import os.path +from tempfile import gettempdir from absl import app from absl import flags @@ -42,8 +43,8 @@ task = Task.init(project_name='examples', task_name='tensorboard pr_curve') tf.compat.v1.disable_v2_behavior() FLAGS = flags.FLAGS - -flags.DEFINE_string('logdir', '/tmp/pr_curve_demo', 'Directory into which to write TensorBoard data.') +flags.DEFINE_string('logdir', os.path.join(gettempdir(), "pr_curve_demo"), + "Directory into which to write TensorBoard data.") flags.DEFINE_integer('steps', 10, 'Number of steps to generate for each PR curve.')