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| | import click.testing |
| | import numpy as np |
| | import os |
| | import tempfile |
| | import unittest |
| |
|
| | from caffe2.python import brew, core, model_helper |
| | import caffe2.contrib.tensorboard.tensorboard as tb |
| | import caffe2.contrib.tensorboard.tensorboard_exporter as tb_exporter |
| |
|
| | try: |
| | |
| | from tensorboard.compat.proto.graph_pb2 import GraphDef |
| | except ImportError: |
| | from tensorflow import GraphDef |
| |
|
| |
|
| | def load_events(filename): |
| | try: |
| | |
| | from tensorboard.backend.event_processing import event_file_loader |
| | loader = event_file_loader.EventFileLoader(filename) |
| | return list(loader.Load()) |
| | except ImportError: |
| | import tensorflow as tf |
| | return list(tf.train.summary_iterator(filename)) |
| |
|
| |
|
| | class TensorboardTest(unittest.TestCase): |
| |
|
| | def test_events(self): |
| | runner = click.testing.CliRunner() |
| | c2_dir = tempfile.mkdtemp() |
| | np.random.seed(1701) |
| | n_iters = 2 |
| | blobs = ["w", "b"] |
| | data = np.random.randn(len(blobs), n_iters, 10) |
| | for i, blob in enumerate(blobs): |
| | with open(os.path.join(c2_dir, blob), "w") as f: |
| | for row in data[i]: |
| | stats = [row.min(), row.max(), row.mean(), row.std()] |
| | f.write(" ".join(str(s) for s in stats) + "\n") |
| |
|
| | |
| | with open(os.path.join(c2_dir, "not-a-summary"), "w") as f: |
| | f.write("not-a-summary") |
| |
|
| | tf_dir = tempfile.mkdtemp() |
| | result = runner.invoke( |
| | tb.cli, |
| | ["tensorboard-events", "--c2-dir", c2_dir, "--tf-dir", tf_dir]) |
| | self.assertEqual(result.exit_code, 0) |
| | entries = list(os.walk(tf_dir)) |
| | self.assertEqual(len(entries), 1) |
| | ((d, _, (fname,)),) = entries |
| | self.assertEqual(tf_dir, d) |
| | events = load_events(os.path.join(tf_dir, fname)) |
| | self.assertEqual(len(events), n_iters + 1) |
| | events = events[1:] |
| | self.maxDiff = None |
| | self.assertEqual(len(events), 2) |
| |
|
| | def test_tensorboard_graphs(self): |
| | model = model_helper.ModelHelper(name="overfeat") |
| | data, label = brew.image_input( |
| | model, ["db"], ["data", "label"], is_test=0 |
| | ) |
| | with core.NameScope("conv1"): |
| | conv1 = brew.conv(model, data, "conv1", 3, 96, 11, stride=4) |
| | relu1 = brew.relu(model, conv1, conv1) |
| | pool1 = brew.max_pool(model, relu1, "pool1", kernel=2, stride=2) |
| | with core.NameScope("classifier"): |
| | fc = brew.fc(model, pool1, "fc", 4096, 1000) |
| | pred = brew.softmax(model, fc, "pred") |
| | xent = model.LabelCrossEntropy([pred, label], "xent") |
| | loss = model.AveragedLoss(xent, "loss") |
| | model.AddGradientOperators([loss], skip=1) |
| |
|
| | c2_dir = tempfile.mkdtemp() |
| | tf_dir = tempfile.mkdtemp() |
| |
|
| | with open(os.path.join(c2_dir, "init"), "w") as f: |
| | f.write(str(model.param_init_net.Proto())) |
| | with open(os.path.join(c2_dir, "net"), "w") as f: |
| | f.write(str(model.net.Proto())) |
| | runner = click.testing.CliRunner() |
| | result = runner.invoke( |
| | tb.cli, |
| | ["tensorboard-graphs", |
| | "--c2-netdef", os.path.join(c2_dir, "init"), |
| | "--c2-netdef", os.path.join(c2_dir, "net"), |
| | "--tf-dir", tf_dir]) |
| | self.assertEqual(result.exit_code, 0) |
| | entries = list(os.walk(tf_dir)) |
| | self.assertEqual(len(entries), 1) |
| | ((d, _, (fname,)),) = entries |
| | self.assertEqual(tf_dir, d) |
| | events = load_events(os.path.join(tf_dir, fname)) |
| | self.assertEqual(len(events), 3) |
| | events = events[1:] |
| | nets = [model.param_init_net, model.net] |
| | for i, (event, net) in enumerate(zip(events, nets), start=1): |
| | self.assertEqual(event.step, i) |
| | self.assertEqual(event.wall_time, i) |
| | g = GraphDef() |
| | g.ParseFromString(event.graph_def) |
| | self.assertMultiLineEqual( |
| | str(g), |
| | str(tb_exporter.nets_to_graph_def([net]))) |
| |
|
| |
|
| | if __name__ == "__main__": |
| | unittest.main() |
| |
|
