Hyperparameter tuning with Ray Tune

Hyperparameter tuning can make the difference between an average model and a highly accurate one. Often simple things like choosing a different learning rate or changing a network layer size can have a dramatic impact on your model performance.

Fortunately, there are tools that help with finding the best combination of parameters. Ray Tune is an industry standard tool for distributed hyperparameter tuning. Ray Tune includes the latest hyperparameter search algorithms, integrates with TensorBoard and other analysis libraries, and natively supports distributed training through Ray’s distributed machine learning engine.

In this tutorial, we will show you how to integrate Ray Tune into your PyTorch training workflow. We will extend this tutorial from the PyTorch documentation for training a CIFAR10 image classifier.

As you will see, we only need to add some slight modifications. In particular, we need to

1. wrap data loading and training in functions,
2. make some network parameters configurable,
3. add checkpointing (optional),
4. and define the search space for the model tuning

To run this tutorial, please make sure the following packages are installed:

• ray[tune]: Distributed hyperparameter tuning library
• torchvision: For the data transformers

Setup / Imports

Let’s start with the imports:

from functools import partial
import numpy as np
import os
import torch
import torch.nn as nn
import torch.nn.functional as F
import torch.optim as optim
from torch.utils.data import random_split
import torchvision
import torchvision.transforms as transforms
from ray import tune
from ray.tune import CLIReporter
from ray.tune.schedulers import ASHAScheduler

Most of the imports are needed for building the PyTorch model. Only the last three imports are for Ray Tune.

Data loaders

We wrap the data loaders in their own function and pass a global data directory. This way we can share a data directory between different trials.

def load_data(data_dir="./data"):
    transform = transforms.Compose([
        transforms.ToTensor(),
        transforms.Normalize((0.5, 0.5, 0.5), (0.5, 0.5, 0.5))
    ])

    trainset = torchvision.datasets.CIFAR10(
        root=data_dir, train=True, download=True, transform=transform)

    testset = torchvision.datasets.CIFAR10(
        root=data_dir, train=False, download=True, transform=transform)

    return trainset, testset

Configurable neural network

We can only tune those parameters that are configurable. In this example, we can specify the layer sizes of the fully connected layers:

class Net(nn.Module):
    def __init__(self, l1=120, l2=84):
        super(Net, self).__init__()
        self.conv1 = nn.Conv2d(3, 6, 5)
        self.pool = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(6, 16, 5)
        self.fc1 = nn.Linear(16 * 5 * 5, l1)
        self.fc2 = nn.Linear(l1, l2)
        self.fc3 = nn.Linear(l2, 10)

    def forward(self, x):
        x = self.pool(F.relu(self.conv1(x)))
        x = self.pool(F.relu(self.conv2(x)))
        x = x.view(-1, 16 * 5 * 5)
        x = F.relu(self.fc1(x))
        x = F.relu(self.fc2(x))
        x = self.fc3(x)
        return x

The train function

Now it gets interesting, because we introduce some changes to the example from the PyTorch documentation.

We wrap the training script in a function train_cifar(config, checkpoint_dir=None, data_dir=None). As you can guess, the config parameter will receive the hyperparameters we would like to train with. The checkpoint_dir parameter is used to restore checkpoints. The data_dir specifies the directory where we load and store the data, so multiple runs can share the same data source.

net = Net(config["l1"], config["l2"])

if checkpoint_dir:
    model_state, optimizer_state = torch.load(
        os.path.join(checkpoint_dir, "checkpoint"))
    net.load_state_dict(model_state)
    optimizer.load_state_dict(optimizer_state)

The learning rate of the optimizer is made configurable, too:

optimizer = optim.SGD(net.parameters(), lr=config["lr"], momentum=0.9)

We also split the training data into a training and validation subset. We thus train on 80% of the data and calculate the validation loss on the remaining 20%. The batch sizes with which we iterate through the training and test sets are configurable as well.

Adding (multi) GPU support with DataParallel

Image classification benefits largely from GPUs. Luckily, we can continue to use PyTorch’s abstractions in Ray Tune. Thus, we can wrap our model in nn.DataParallel to support data parallel training on multiple GPUs:

device = "cpu"
if torch.cuda.is_available():
    device = "cuda:0"
    if torch.cuda.device_count() > 1:
        net = nn.DataParallel(net)
net.to(device)

By using a device variable we make sure that training also works when we have no GPUs available. PyTorch requires us to send our data to the GPU memory explicitly, like this:

for i, data in enumerate(trainloader, 0):
    inputs, labels = data
    inputs, labels = inputs.to(device), labels.to(device)

The code now supports training on CPUs, on a single GPU, and on multiple GPUs. Notably, Ray also supports fractional GPUs so we can share GPUs among trials, as long as the model still fits on the GPU memory. We’ll come back to that later.

Communicating with Ray Tune

The most interesting part is the communication with Ray Tune:

with tune.checkpoint_dir(epoch) as checkpoint_dir:
    path = os.path.join(checkpoint_dir, "checkpoint")
    torch.save((net.state_dict(), optimizer.state_dict()), path)

tune.report(loss=(val_loss / val_steps), accuracy=correct / total)

Here we first save a checkpoint and then report some metrics back to Ray Tune. Specifically, we send the validation loss and accuracy back to Ray Tune. Ray Tune can then use these metrics to decide which hyperparameter configuration lead to the best results. These metrics can also be used to stop bad performing trials early in order to avoid wasting resources on those trials.

The checkpoint saving is optional, however, it is necessary if we wanted to use advanced schedulers like Population Based Training. Also, by saving the checkpoint we can later load the trained models and validate them on a test set.

Full training function

The full code example looks like this:

def train_cifar(config, checkpoint_dir=None, data_dir=None):
    net = Net(config["l1"], config["l2"])

    device = "cpu"
    if torch.cuda.is_available():
        device = "cuda:0"
        if torch.cuda.device_count() > 1:
            net = nn.DataParallel(net)
    net.to(device)

    criterion = nn.CrossEntropyLoss()
    optimizer = optim.SGD(net.parameters(), lr=config["lr"], momentum=0.9)

    if checkpoint_dir:
        model_state, optimizer_state = torch.load(
            os.path.join(checkpoint_dir, "checkpoint"))
        net.load_state_dict(model_state)
        optimizer.load_state_dict(optimizer_state)

    trainset, testset = load_data(data_dir)

    test_abs = int(len(trainset) * 0.8)
    train_subset, val_subset = random_split(
        trainset, [test_abs, len(trainset) - test_abs])

    trainloader = torch.utils.data.DataLoader(
        train_subset,
        batch_size=int(config["batch_size"]),
        shuffle=True,
        num_workers=8)
    valloader = torch.utils.data.DataLoader(
        val_subset,
        batch_size=int(config["batch_size"]),
        shuffle=True,
        num_workers=8)

    for epoch in range(10):  # loop over the dataset multiple times
        running_loss = 0.0
        epoch_steps = 0
        for i, data in enumerate(trainloader, 0):
            # get the inputs; data is a list of [inputs, labels]
            inputs, labels = data
            inputs, labels = inputs.to(device), labels.to(device)

            # zero the parameter gradients
            optimizer.zero_grad()

            # forward + backward + optimize
            outputs = net(inputs)
            loss = criterion(outputs, labels)
            loss.backward()
            optimizer.step()

            # print statistics
            running_loss += loss.item()
            epoch_steps += 1
            if i % 2000 == 1999:  # print every 2000 mini-batches
                print("[%d, %5d] loss: %.3f" % (epoch + 1, i + 1,
                                                running_loss / epoch_steps))
                running_loss = 0.0

        # Validation loss
        val_loss = 0.0
        val_steps = 0
        total = 0
        correct = 0
        for i, data in enumerate(valloader, 0):
            with torch.no_grad():
                inputs, labels = data
                inputs, labels = inputs.to(device), labels.to(device)

                outputs = net(inputs)
                _, predicted = torch.max(outputs.data, 1)
                total += labels.size(0)
                correct += (predicted == labels).sum().item()

                loss = criterion(outputs, labels)
                val_loss += loss.cpu().numpy()
                val_steps += 1

        with tune.checkpoint_dir(epoch) as checkpoint_dir:
            path = os.path.join(checkpoint_dir, "checkpoint")
            torch.save((net.state_dict(), optimizer.state_dict()), path)

        tune.report(loss=(val_loss / val_steps), accuracy=correct / total)
    print("Finished Training")

As you can see, most of the code is adapted directly from the original example.

Test set accuracy

Commonly the performance of a machine learning model is tested on a hold-out test set with data that has not been used for training the model. We also wrap this in a function:

def test_accuracy(net, device="cpu"):
    trainset, testset = load_data()

    testloader = torch.utils.data.DataLoader(
        testset, batch_size=4, shuffle=False, num_workers=2)

    correct = 0
    total = 0
    with torch.no_grad():
        for data in testloader:
            images, labels = data
            images, labels = images.to(device), labels.to(device)
            outputs = net(images)
            _, predicted = torch.max(outputs.data, 1)
            total += labels.size(0)
            correct += (predicted == labels).sum().item()

    return correct / total

The function also expects a device parameter, so we can do the test set validation on a GPU.

Configuring the search space

Lastly, we need to define Ray Tune’s search space. Here is an example:

config = {
    "l1": tune.sample_from(lambda _: 2**np.random.randint(2, 9)),
    "l2": tune.sample_from(lambda _: 2**np.random.randint(2, 9)),
    "lr": tune.loguniform(1e-4, 1e-1),
    "batch_size": tune.choice([2, 4, 8, 16])
}

The tune.sample_from() function makes it possible to define your own sample methods to obtain hyperparameters. In this example, the l1 and l2 parameters should be powers of 2 between 4 and 256, so either 4, 8, 16, 32, 64, 128, or 256. The lr (learning rate) should be uniformly sampled between 0.0001 and 0.1. Lastly, the batch size is a choice between 2, 4, 8, and 16.

At each trial, Ray Tune will now randomly sample a combination of parameters from these search spaces. It will then train a number of models in parallel and find the best performing one among these. We also use the ASHAScheduler which will terminate bad performing trials early.

We wrap the train_cifar function with functools.partial to set the constant data_dir parameter. We can also tell Ray Tune what resources should be available for each trial:

gpus_per_trial = 2
# ...
result = tune.run(
    partial(train_cifar, data_dir=data_dir),
    resources_per_trial={"cpu": 8, "gpu": gpus_per_trial},
    config=config,
    num_samples=num_samples,
    scheduler=scheduler,
    progress_reporter=reporter,
    checkpoint_at_end=True)

You can specify the number of CPUs, which are then available e.g. to increase the num_workers of the PyTorch DataLoader instances. The selected number of GPUs are made visible to PyTorch in each trial. Trials do not have access to GPUs that haven’t been requested for them - so you don’t have to care about two trials using the same set of resources.

Here we can also specify fractional GPUs, so something like gpus_per_trial=0.5 is completely valid. The trials will then share GPUs among each other. You just have to make sure that the models still fit in the GPU memory.

After training the models, we will find the best performing one and load the trained network from the checkpoint file. We then obtain the test set accuracy and report everything by printing.

The full main function looks like this:

def main(num_samples=10, max_num_epochs=10, gpus_per_trial=2):
    data_dir = os.path.abspath("./data")
    load_data(data_dir)
    config = {
        "l1": tune.sample_from(lambda _: 2 ** np.random.randint(2, 9)),
        "l2": tune.sample_from(lambda _: 2 ** np.random.randint(2, 9)),
        "lr": tune.loguniform(1e-4, 1e-1),
        "batch_size": tune.choice([2, 4, 8, 16])
    }
    scheduler = ASHAScheduler(
        metric="loss",
        mode="min",
        max_t=max_num_epochs,
        grace_period=1,
        reduction_factor=2)
    reporter = CLIReporter(
        # parameter_columns=["l1", "l2", "lr", "batch_size"],
        metric_columns=["loss", "accuracy", "training_iteration"])
    result = tune.run(
        partial(train_cifar, data_dir=data_dir),
        resources_per_trial={"cpu": 2, "gpu": gpus_per_trial},
        config=config,
        num_samples=num_samples,
        scheduler=scheduler,
        progress_reporter=reporter)

    best_trial = result.get_best_trial("loss", "min", "last")
    print("Best trial config: {}".format(best_trial.config))
    print("Best trial final validation loss: {}".format(
        best_trial.last_result["loss"]))
    print("Best trial final validation accuracy: {}".format(
        best_trial.last_result["accuracy"]))

    best_trained_model = Net(best_trial.config["l1"], best_trial.config["l2"])
    device = "cpu"
    if torch.cuda.is_available():
        device = "cuda:0"
        if gpus_per_trial > 1:
            best_trained_model = nn.DataParallel(best_trained_model)
    best_trained_model.to(device)

    best_checkpoint_dir = best_trial.checkpoint.value
    model_state, optimizer_state = torch.load(os.path.join(
        best_checkpoint_dir, "checkpoint"))
    best_trained_model.load_state_dict(model_state)

    test_acc = test_accuracy(best_trained_model, device)
    print("Best trial test set accuracy: {}".format(test_acc))


if __name__ == "__main__":
    # You can change the number of GPUs per trial here:
    main(num_samples=10, max_num_epochs=10, gpus_per_trial=0)

Out:

Downloading https://www.cs.toronto.edu/~kriz/cifar-10-python.tar.gz to /var/lib/jenkins/workspace/beginner_source/data/cifar-10-python.tar.gz
Extracting /var/lib/jenkins/workspace/beginner_source/data/cifar-10-python.tar.gz to /var/lib/jenkins/workspace/beginner_source/data
Files already downloaded and verified
== Status ==
Memory usage on this node: 4.1/240.1 GiB
Using AsyncHyperBand: num_stopped=0
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: None | Iter 1.000: None
Resources requested: 2/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 1/10 (1 RUNNING)
+---------------------+----------+-------+--------------+------+------+------------+
| Trial name          | status   | loc   |   batch_size |   l1 |   l2 |         lr |
|---------------------+----------+-------+--------------+------+------+------------|
| DEFAULT_da74d_00000 | RUNNING  |       |            8 |   64 |  256 | 0.00646798 |
+---------------------+----------+-------+--------------+------+------+------------+


(pid=1419) Files already downloaded and verified
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(pid=1454) [1,  2000] loss: 2.262
(pid=1421) [1,  2000] loss: 2.196
(pid=1430) [1,  2000] loss: 2.322
(pid=1447) [1,  2000] loss: 2.348
(pid=1457) [1,  2000] loss: 2.150
(pid=1419) [1,  2000] loss: 1.875
(pid=1420) [1,  2000] loss: 1.951
(pid=1422) [1,  2000] loss: 2.102
(pid=1415) [1,  2000] loss: 2.255
(pid=1446) [1,  2000] loss: 2.311
(pid=1454) [1,  4000] loss: 1.039
(pid=1421) [1,  4000] loss: 1.006
(pid=1430) [1,  4000] loss: 1.154
Result for DEFAULT_da74d_00001:
  accuracy: 0.1503
  date: 2021-02-26_20-26-35
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 2.2887174449920655
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 27.85807466506958
  time_this_iter_s: 27.85807466506958
  time_total_s: 27.85807466506958
  timestamp: 1614371195
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 9.2/240.1 GiB
Using AsyncHyperBand: num_stopped=0
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: None | Iter 1.000: -2.2887174449920655
Resources requested: 20/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (10 RUNNING)
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status   | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING  |                 |            8 |   64 |  256 | 0.00646798  |         |            |                      |
| DEFAULT_da74d_00001 | RUNNING  | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 2.28872 |     0.1503 |                    1 |
| DEFAULT_da74d_00002 | RUNNING  |                 |            4 |   64 |   64 | 0.0142423   |         |            |                      |
| DEFAULT_da74d_00003 | RUNNING  |                 |            8 |    8 |  256 | 0.0150371   |         |            |                      |
| DEFAULT_da74d_00004 | RUNNING  |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING  |                 |            8 |    8 |  128 | 0.0108518   |         |            |                      |
| DEFAULT_da74d_00006 | RUNNING  |                 |            4 |    4 |    4 | 0.079216    |         |            |                      |
| DEFAULT_da74d_00007 | RUNNING  |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING  |                 |            8 |   32 |    8 | 0.000820594 |         |            |                      |
| DEFAULT_da74d_00009 | RUNNING  |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1447) [1,  4000] loss: 1.174
(pid=1457) [1,  4000] loss: 1.063
(pid=1420) [1,  4000] loss: 0.898
(pid=1422) [1,  4000] loss: 1.011
(pid=1415) [1,  4000] loss: 0.948
(pid=1419) [1,  4000] loss: 0.802
(pid=1454) [1,  6000] loss: 0.661
(pid=1430) [1,  6000] loss: 0.768
(pid=1421) [1,  6000] loss: 0.634
(pid=1447) [1,  6000] loss: 0.782
(pid=1457) [1,  6000] loss: 0.717
Result for DEFAULT_da74d_00005:
  accuracy: 0.3615
  date: 2021-02-26_20-26-49
  done: false
  experiment_id: dd72d2f0d9784a71972ef69ab60db084
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 1.7052976821899415
  node_ip: 172.17.0.2
  pid: 1420
  should_checkpoint: true
  time_since_restore: 42.42658591270447
  time_this_iter_s: 42.42658591270447
  time_total_s: 42.42658591270447
  timestamp: 1614371209
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00005

== Status ==
Memory usage on this node: 9.3/240.1 GiB
Using AsyncHyperBand: num_stopped=0
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: None | Iter 1.000: -1.9970075635910036
Resources requested: 20/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (10 RUNNING)
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status   | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING  |                 |            8 |   64 |  256 | 0.00646798  |         |            |                      |
| DEFAULT_da74d_00001 | RUNNING  | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 2.28872 |     0.1503 |                    1 |
| DEFAULT_da74d_00002 | RUNNING  |                 |            4 |   64 |   64 | 0.0142423   |         |            |                      |
| DEFAULT_da74d_00003 | RUNNING  |                 |            8 |    8 |  256 | 0.0150371   |         |            |                      |
| DEFAULT_da74d_00004 | RUNNING  |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING  | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.7053  |     0.3615 |                    1 |
| DEFAULT_da74d_00006 | RUNNING  |                 |            4 |    4 |    4 | 0.079216    |         |            |                      |
| DEFAULT_da74d_00007 | RUNNING  |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING  |                 |            8 |   32 |    8 | 0.000820594 |         |            |                      |
| DEFAULT_da74d_00009 | RUNNING  |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
+---------------------+----------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00003:
  accuracy: 0.1835
  date: 2021-02-26_20-26-50
  done: true
  experiment_id: d32ef5791fc148498c5005dd2f09277a
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 2.072287780284882
  node_ip: 172.17.0.2
  pid: 1422
  should_checkpoint: true
  time_since_restore: 42.821146965026855
  time_this_iter_s: 42.821146965026855
  time_total_s: 42.821146965026855
  timestamp: 1614371210
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00003

Result for DEFAULT_da74d_00008:
  accuracy: 0.3868
  date: 2021-02-26_20-26-50
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 1.6864227166652679
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 43.11535668373108
  time_this_iter_s: 43.11535668373108
  time_total_s: 43.11535668373108
  timestamp: 1614371210
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00008

Result for DEFAULT_da74d_00000:
  accuracy: 0.4418
  date: 2021-02-26_20-26-50
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 1.525510474061966
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 43.45280838012695
  time_this_iter_s: 43.45280838012695
  time_total_s: 43.45280838012695
  timestamp: 1614371210
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00000

(pid=1446) [2,  2000] loss: 2.236
(pid=1454) [1,  8000] loss: 0.482
(pid=1421) [1,  8000] loss: 0.445
(pid=1430) [1,  8000] loss: 0.576
Result for DEFAULT_da74d_00001:
  accuracy: 0.2261
  date: 2021-02-26_20-26-59
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 2
  loss: 2.092621375656128
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 52.07927751541138
  time_this_iter_s: 24.221202850341797
  time_total_s: 52.07927751541138
  timestamp: 1614371219
  timesteps_since_restore: 0
  training_iteration: 2
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 8.8/240.1 GiB
Using AsyncHyperBand: num_stopped=1
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -2.092621375656128 | Iter 1.000: -1.7052976821899415
Resources requested: 18/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (9 RUNNING, 1 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.52551 |     0.4418 |                    1 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 2.09262 |     0.2261 |                    2 |
| DEFAULT_da74d_00002 | RUNNING    |                 |            4 |   64 |   64 | 0.0142423   |         |            |                      |
| DEFAULT_da74d_00004 | RUNNING    |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.7053  |     0.3615 |                    1 |
| DEFAULT_da74d_00006 | RUNNING    |                 |            4 |    4 |    4 | 0.079216    |         |            |                      |
| DEFAULT_da74d_00007 | RUNNING    |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.68642 |     0.3868 |                    1 |
| DEFAULT_da74d_00009 | RUNNING    |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1447) [1,  8000] loss: 0.588
(pid=1457) [1,  8000] loss: 0.529
(pid=1420) [2,  2000] loss: 1.770
(pid=1415) [2,  2000] loss: 1.658
(pid=1419) [2,  2000] loss: 1.489
(pid=1454) [1, 10000] loss: 0.375
(pid=1421) [1, 10000] loss: 0.346
(pid=1430) [1, 10000] loss: 0.460
(pid=1447) [1, 10000] loss: 0.470
(pid=1457) [1, 10000] loss: 0.428
(pid=1446) [3,  2000] loss: 1.989
(pid=1420) [2,  4000] loss: 0.887
(pid=1454) [1, 12000] loss: 0.314
(pid=1415) [2,  4000] loss: 0.781
(pid=1421) [1, 12000] loss: 0.280
(pid=1430) [1, 12000] loss: 0.384
(pid=1419) [2,  4000] loss: 0.743
Result for DEFAULT_da74d_00006:
  accuracy: 0.1005
  date: 2021-02-26_20-27-19
  done: true
  experiment_id: e40403f57743415d86dda9607f2449c6
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 2.3291412625312806
  node_ip: 172.17.0.2
  pid: 1447
  should_checkpoint: true
  time_since_restore: 71.89647650718689
  time_this_iter_s: 71.89647650718689
  time_total_s: 71.89647650718689
  timestamp: 1614371239
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00006

== Status ==
Memory usage on this node: 8.9/240.1 GiB
Using AsyncHyperBand: num_stopped=2
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -2.092621375656128 | Iter 1.000: -1.8887927312374115
Resources requested: 18/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (9 RUNNING, 1 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.52551 |     0.4418 |                    1 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 2.09262 |     0.2261 |                    2 |
| DEFAULT_da74d_00002 | RUNNING    |                 |            4 |   64 |   64 | 0.0142423   |         |            |                      |
| DEFAULT_da74d_00004 | RUNNING    |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.7053  |     0.3615 |                    1 |
| DEFAULT_da74d_00006 | RUNNING    | 172.17.0.2:1447 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00007 | RUNNING    |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.68642 |     0.3868 |                    1 |
| DEFAULT_da74d_00009 | RUNNING    |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00002:
  accuracy: 0.1267
  date: 2021-02-26_20-27-21
  done: true
  experiment_id: a5b519cc84fb46ba9f4299788360832b
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 2.1816043051719665
  node_ip: 172.17.0.2
  pid: 1457
  should_checkpoint: true
  time_since_restore: 74.21312308311462
  time_this_iter_s: 74.21312308311462
  time_total_s: 74.21312308311462
  timestamp: 1614371241
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00002

Result for DEFAULT_da74d_00001:
  accuracy: 0.3239
  date: 2021-02-26_20-27-22
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 3
  loss: 1.8586337614059447
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 75.3482575416565
  time_this_iter_s: 23.268980026245117
  time_total_s: 75.3482575416565
  timestamp: 1614371242
  timesteps_since_restore: 0
  training_iteration: 3
  trial_id: da74d_00001

(pid=1454) [1, 14000] loss: 0.264
Result for DEFAULT_da74d_00005:
  accuracy: 0.3543
  date: 2021-02-26_20-27-26
  done: false
  experiment_id: dd72d2f0d9784a71972ef69ab60db084
  hostname: 0b92e671318e
  iterations_since_restore: 2
  loss: 1.7419664831638335
  node_ip: 172.17.0.2
  pid: 1420
  should_checkpoint: true
  time_since_restore: 79.20708870887756
  time_this_iter_s: 36.780502796173096
  time_total_s: 79.20708870887756
  timestamp: 1614371246
  timesteps_since_restore: 0
  training_iteration: 2
  trial_id: da74d_00005

== Status ==
Memory usage on this node: 7.8/240.1 GiB
Using AsyncHyperBand: num_stopped=3
Bracket: Iter 8.000: None | Iter 4.000: None | Iter 2.000: -1.9172939294099807 | Iter 1.000: -2.072287780284882
Resources requested: 14/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (7 RUNNING, 3 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.52551 |     0.4418 |                    1 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.85863 |     0.3239 |                    3 |
| DEFAULT_da74d_00004 | RUNNING    |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.74197 |     0.3543 |                    2 |
| DEFAULT_da74d_00007 | RUNNING    |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.68642 |     0.3868 |                    1 |
| DEFAULT_da74d_00009 | RUNNING    |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1421) [1, 14000] loss: 0.238
Result for DEFAULT_da74d_00008:
  accuracy: 0.4698
  date: 2021-02-26_20-27-27
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 2
  loss: 1.459486995410919
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 80.27314257621765
  time_this_iter_s: 37.15778589248657
  time_total_s: 80.27314257621765
  timestamp: 1614371247
  timesteps_since_restore: 0
  training_iteration: 2
  trial_id: da74d_00008

(pid=1430) [1, 14000] loss: 0.328
Result for DEFAULT_da74d_00000:
  accuracy: 0.4625
  date: 2021-02-26_20-27-28
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 2
  loss: 1.4884922024250031
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 80.99731063842773
  time_this_iter_s: 37.54450225830078
  time_total_s: 80.99731063842773
  timestamp: 1614371248
  timesteps_since_restore: 0
  training_iteration: 2
  trial_id: da74d_00000

(pid=1454) [1, 16000] loss: 0.230
(pid=1421) [1, 16000] loss: 0.204
(pid=1430) [1, 16000] loss: 0.287
(pid=1446) [4,  2000] loss: 1.780
(pid=1420) [3,  2000] loss: 1.779
(pid=1415) [3,  2000] loss: 1.464
(pid=1419) [3,  2000] loss: 1.416
Result for DEFAULT_da74d_00001:
  accuracy: 0.3797
  date: 2021-02-26_20-27-44
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 4
  loss: 1.670368455696106
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 97.65018343925476
  time_this_iter_s: 22.301925897598267
  time_total_s: 97.65018343925476
  timestamp: 1614371264
  timesteps_since_restore: 0
  training_iteration: 4
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 7.8/240.1 GiB
Using AsyncHyperBand: num_stopped=3
Bracket: Iter 8.000: None | Iter 4.000: -1.670368455696106 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -2.072287780284882
Resources requested: 14/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (7 RUNNING, 3 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.48849 |     0.4625 |                    2 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.67037 |     0.3797 |                    4 |
| DEFAULT_da74d_00004 | RUNNING    |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.74197 |     0.3543 |                    2 |
| DEFAULT_da74d_00007 | RUNNING    |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.45949 |     0.4698 |                    2 |
| DEFAULT_da74d_00009 | RUNNING    |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1454) [1, 18000] loss: 0.207
(pid=1421) [1, 18000] loss: 0.182
(pid=1430) [1, 18000] loss: 0.253
(pid=1420) [3,  4000] loss: 0.898
(pid=1415) [3,  4000] loss: 0.707
(pid=1419) [3,  4000] loss: 0.716
(pid=1454) [1, 20000] loss: 0.187
(pid=1421) [1, 20000] loss: 0.163
(pid=1430) [1, 20000] loss: 0.226
(pid=1446) [5,  2000] loss: 1.639
Result for DEFAULT_da74d_00005:
  accuracy: 0.3168
  date: 2021-02-26_20-28-01
  done: false
  experiment_id: dd72d2f0d9784a71972ef69ab60db084
  hostname: 0b92e671318e
  iterations_since_restore: 3
  loss: 1.8536528338909148
  node_ip: 172.17.0.2
  pid: 1420
  should_checkpoint: true
  time_since_restore: 114.06767654418945
  time_this_iter_s: 34.86058783531189
  time_total_s: 114.06767654418945
  timestamp: 1614371281
  timesteps_since_restore: 0
  training_iteration: 3
  trial_id: da74d_00005

== Status ==
Memory usage on this node: 7.9/240.1 GiB
Using AsyncHyperBand: num_stopped=3
Bracket: Iter 8.000: None | Iter 4.000: -1.670368455696106 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -2.072287780284882
Resources requested: 14/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (7 RUNNING, 3 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.48849 |     0.4625 |                    2 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.67037 |     0.3797 |                    4 |
| DEFAULT_da74d_00004 | RUNNING    |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.85365 |     0.3168 |                    3 |
| DEFAULT_da74d_00007 | RUNNING    |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.45949 |     0.4698 |                    2 |
| DEFAULT_da74d_00009 | RUNNING    |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00008:
  accuracy: 0.474
  date: 2021-02-26_20-28-03
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 3
  loss: 1.4891104881763457
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 115.78469705581665
  time_this_iter_s: 35.511554479599
  time_total_s: 115.78469705581665
  timestamp: 1614371283
  timesteps_since_restore: 0
  training_iteration: 3
  trial_id: da74d_00008

Result for DEFAULT_da74d_00000:
  accuracy: 0.4856
  date: 2021-02-26_20-28-04
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 3
  loss: 1.4677546185016632
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 117.28643274307251
  time_this_iter_s: 36.289122104644775
  time_total_s: 117.28643274307251
  timestamp: 1614371284
  timesteps_since_restore: 0
  training_iteration: 3
  trial_id: da74d_00000

Result for DEFAULT_da74d_00001:
  accuracy: 0.4147
  date: 2021-02-26_20-28-07
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 5
  loss: 1.5820930083274842
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 120.34646391868591
  time_this_iter_s: 22.696280479431152
  time_total_s: 120.34646391868591
  timestamp: 1614371287
  timesteps_since_restore: 0
  training_iteration: 5
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 7.9/240.1 GiB
Using AsyncHyperBand: num_stopped=3
Bracket: Iter 8.000: None | Iter 4.000: -1.670368455696106 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -2.072287780284882
Resources requested: 14/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (7 RUNNING, 3 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.46775 |     0.4856 |                    3 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.58209 |     0.4147 |                    5 |
| DEFAULT_da74d_00004 | RUNNING    |                 |            2 |    4 |    4 | 0.000303051 |         |            |                      |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.85365 |     0.3168 |                    3 |
| DEFAULT_da74d_00007 | RUNNING    |                 |            2 |    4 |   32 | 0.00104518  |         |            |                      |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.48911 |     0.474  |                    3 |
| DEFAULT_da74d_00009 | RUNNING    |                 |            2 |    8 |   32 | 0.00276505  |         |            |                      |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00009:
  accuracy: 0.2768
  date: 2021-02-26_20-28-09
  done: false
  experiment_id: 7a996ae85ee84cd5befcf6252e7ef6d4
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 1.9227685967683792
  node_ip: 172.17.0.2
  pid: 1454
  should_checkpoint: true
  time_since_restore: 122.37326312065125
  time_this_iter_s: 122.37326312065125
  time_total_s: 122.37326312065125
  timestamp: 1614371289
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00009

Result for DEFAULT_da74d_00007:
  accuracy: 0.3979
  date: 2021-02-26_20-28-10
  done: false
  experiment_id: f38b32d4499a4f59836f13bb7b7095f7
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 1.6090776248946785
  node_ip: 172.17.0.2
  pid: 1421
  should_checkpoint: true
  time_since_restore: 123.21496987342834
  time_this_iter_s: 123.21496987342834
  time_total_s: 123.21496987342834
  timestamp: 1614371290
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00007

Result for DEFAULT_da74d_00004:
  accuracy: 0.1734
  date: 2021-02-26_20-28-11
  done: true
  experiment_id: c3beafe7c9434d4490237fa65cfe1f11
  hostname: 0b92e671318e
  iterations_since_restore: 1
  loss: 2.2460573588371275
  node_ip: 172.17.0.2
  pid: 1430
  should_checkpoint: true
  time_since_restore: 123.91765284538269
  time_this_iter_s: 123.91765284538269
  time_total_s: 123.91765284538269
  timestamp: 1614371291
  timesteps_since_restore: 0
  training_iteration: 1
  trial_id: da74d_00004

(pid=1420) [4,  2000] loss: 1.790
(pid=1415) [4,  2000] loss: 1.344
(pid=1419) [4,  2000] loss: 1.366
(pid=1454) [2,  2000] loss: 1.819
(pid=1421) [2,  2000] loss: 1.600
(pid=1446) [6,  2000] loss: 1.548
(pid=1420) [4,  4000] loss: 0.927
(pid=1415) [4,  4000] loss: 0.668
(pid=1454) [2,  4000] loss: 0.930
Result for DEFAULT_da74d_00001:
  accuracy: 0.4353
  date: 2021-02-26_20-28-29
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 6
  loss: 1.5407315127372743
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 142.0170876979828
  time_this_iter_s: 21.670623779296875
  time_total_s: 142.0170876979828
  timestamp: 1614371309
  timesteps_since_restore: 0
  training_iteration: 6
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 7.4/240.1 GiB
Using AsyncHyperBand: num_stopped=4
Bracket: Iter 8.000: None | Iter 4.000: -1.670368455696106 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 12/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (6 RUNNING, 4 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.46775 |     0.4856 |                    3 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.54073 |     0.4353 |                    6 |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.85365 |     0.3168 |                    3 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.48911 |     0.474  |                    3 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1419) [4,  4000] loss: 0.700
(pid=1421) [2,  4000] loss: 0.781
Result for DEFAULT_da74d_00005:
  accuracy: 0.2839
  date: 2021-02-26_20-28-35
  done: true
  experiment_id: dd72d2f0d9784a71972ef69ab60db084
  hostname: 0b92e671318e
  iterations_since_restore: 4
  loss: 1.9311893384933472
  node_ip: 172.17.0.2
  pid: 1420
  should_checkpoint: true
  time_since_restore: 148.27433562278748
  time_this_iter_s: 34.20665907859802
  time_total_s: 148.27433562278748
  timestamp: 1614371315
  timesteps_since_restore: 0
  training_iteration: 4
  trial_id: da74d_00005

== Status ==
Memory usage on this node: 7.4/240.1 GiB
Using AsyncHyperBand: num_stopped=5
Bracket: Iter 8.000: None | Iter 4.000: -1.8007788970947267 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 12/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (6 RUNNING, 4 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.46775 |     0.4856 |                    3 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.54073 |     0.4353 |                    6 |
| DEFAULT_da74d_00005 | RUNNING    | 172.17.0.2:1420 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.48911 |     0.474  |                    3 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00008:
  accuracy: 0.5218
  date: 2021-02-26_20-28-38
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 4
  loss: 1.327530821633339
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 150.68803215026855
  time_this_iter_s: 34.903335094451904
  time_total_s: 150.68803215026855
  timestamp: 1614371318
  timesteps_since_restore: 0
  training_iteration: 4
  trial_id: da74d_00008

(pid=1454) [2,  6000] loss: 0.603
(pid=1421) [2,  6000] loss: 0.518
Result for DEFAULT_da74d_00000:
  accuracy: 0.5012
  date: 2021-02-26_20-28-39
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 4
  loss: 1.4394630181789398
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 152.61839723587036
  time_this_iter_s: 35.33196449279785
  time_total_s: 152.61839723587036
  timestamp: 1614371319
  timesteps_since_restore: 0
  training_iteration: 4
  trial_id: da74d_00000

(pid=1446) [7,  2000] loss: 1.488
(pid=1454) [2,  8000] loss: 0.459
(pid=1421) [2,  8000] loss: 0.394
(pid=1415) [5,  2000] loss: 1.277
Result for DEFAULT_da74d_00001:
  accuracy: 0.4645
  date: 2021-02-26_20-28-50
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 7
  loss: 1.4647596702575683
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 163.39900302886963
  time_this_iter_s: 21.38191533088684
  time_total_s: 163.39900302886963
  timestamp: 1614371330
  timesteps_since_restore: 0
  training_iteration: 7
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 6.8/240.1 GiB
Using AsyncHyperBand: num_stopped=5
Bracket: Iter 8.000: None | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 10/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (5 RUNNING, 5 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.43946 |     0.5012 |                    4 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.46476 |     0.4645 |                    7 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.32753 |     0.5218 |                    4 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1419) [5,  2000] loss: 1.325
(pid=1454) [2, 10000] loss: 0.363
(pid=1421) [2, 10000] loss: 0.313
(pid=1415) [5,  4000] loss: 0.625
(pid=1419) [5,  4000] loss: 0.689
(pid=1446) [8,  2000] loss: 1.437
(pid=1454) [2, 12000] loss: 0.297
(pid=1421) [2, 12000] loss: 0.256
Result for DEFAULT_da74d_00008:
  accuracy: 0.5202
  date: 2021-02-26_20-29-11
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 5
  loss: 1.3261634290218354
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 183.65447759628296
  time_this_iter_s: 32.966445446014404
  time_total_s: 183.65447759628296
  timestamp: 1614371351
  timesteps_since_restore: 0
  training_iteration: 5
  trial_id: da74d_00008

== Status ==
Memory usage on this node: 6.9/240.1 GiB
Using AsyncHyperBand: num_stopped=5
Bracket: Iter 8.000: None | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 10/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (5 RUNNING, 5 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.43946 |     0.5012 |                    4 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.46476 |     0.4645 |                    7 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.32616 |     0.5202 |                    5 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00001:
  accuracy: 0.4764
  date: 2021-02-26_20-29-11
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 8
  loss: 1.446412706375122
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 184.39706802368164
  time_this_iter_s: 20.99806499481201
  time_total_s: 184.39706802368164
  timestamp: 1614371351
  timesteps_since_restore: 0
  training_iteration: 8
  trial_id: da74d_00001

Result for DEFAULT_da74d_00000:
  accuracy: 0.4975
  date: 2021-02-26_20-29-13
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 5
  loss: 1.439678263449669
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 186.38049840927124
  time_this_iter_s: 33.76210117340088
  time_total_s: 186.38049840927124
  timestamp: 1614371353
  timesteps_since_restore: 0
  training_iteration: 5
  trial_id: da74d_00000

(pid=1454) [2, 14000] loss: 0.258
(pid=1421) [2, 14000] loss: 0.216
(pid=1415) [6,  2000] loss: 1.212
(pid=1454) [2, 16000] loss: 0.220
(pid=1421) [2, 16000] loss: 0.192
(pid=1419) [6,  2000] loss: 1.329
(pid=1446) [9,  2000] loss: 1.391
Result for DEFAULT_da74d_00001:
  accuracy: 0.5038
  date: 2021-02-26_20-29-32
  done: false
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 9
  loss: 1.3644779193878174
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 205.46153283119202
  time_this_iter_s: 21.064464807510376
  time_total_s: 205.46153283119202
  timestamp: 1614371372
  timesteps_since_restore: 0
  training_iteration: 9
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 7.0/240.1 GiB
Using AsyncHyperBand: num_stopped=5
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 10/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (5 RUNNING, 5 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.43968 |     0.4975 |                    5 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.36448 |     0.5038 |                    9 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.32616 |     0.5202 |                    5 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1454) [2, 18000] loss: 0.201
(pid=1415) [6,  4000] loss: 0.603
(pid=1421) [2, 18000] loss: 0.169
(pid=1419) [6,  4000] loss: 0.680
(pid=1454) [2, 20000] loss: 0.182
(pid=1421) [2, 20000] loss: 0.154
Result for DEFAULT_da74d_00008:
  accuracy: 0.5508
  date: 2021-02-26_20-29-44
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 6
  loss: 1.2812463031530381
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 216.8842477798462
  time_this_iter_s: 33.22977018356323
  time_total_s: 216.8842477798462
  timestamp: 1614371384
  timesteps_since_restore: 0
  training_iteration: 6
  trial_id: da74d_00008

== Status ==
Memory usage on this node: 7.0/240.1 GiB
Using AsyncHyperBand: num_stopped=5
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 10/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (5 RUNNING, 5 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.43968 |     0.4975 |                    5 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.36448 |     0.5038 |                    9 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.28125 |     0.5508 |                    6 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1446) [10,  2000] loss: 1.346
Result for DEFAULT_da74d_00000:
  accuracy: 0.5164
  date: 2021-02-26_20-29-47
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 6
  loss: 1.4101861970424652
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 220.41678524017334
  time_this_iter_s: 34.0362868309021
  time_total_s: 220.41678524017334
  timestamp: 1614371387
  timesteps_since_restore: 0
  training_iteration: 6
  trial_id: da74d_00000

Result for DEFAULT_da74d_00001:
  accuracy: 0.5062
  date: 2021-02-26_20-29-54
  done: true
  experiment_id: a7b8b29cfdab4bb6a59bdaf6229ce657
  hostname: 0b92e671318e
  iterations_since_restore: 10
  loss: 1.3854370698928833
  node_ip: 172.17.0.2
  pid: 1446
  should_checkpoint: true
  time_since_restore: 226.80386519432068
  time_this_iter_s: 21.342332363128662
  time_total_s: 226.80386519432068
  timestamp: 1614371394
  timesteps_since_restore: 0
  training_iteration: 10
  trial_id: da74d_00001

== Status ==
Memory usage on this node: 7.0/240.1 GiB
Using AsyncHyperBand: num_stopped=6
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.6152293427944184 | Iter 1.000: -1.9975281885266305
Resources requested: 10/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (5 RUNNING, 5 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.41019 |     0.5164 |                    6 |
| DEFAULT_da74d_00001 | RUNNING    | 172.17.0.2:1446 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.60908 |     0.3979 |                    1 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.28125 |     0.5508 |                    6 |
| DEFAULT_da74d_00009 | RUNNING    | 172.17.0.2:1454 |            2 |    8 |   32 | 0.00276505  | 1.92277 |     0.2768 |                    1 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00009:
  accuracy: 0.334
  date: 2021-02-26_20-29-54
  done: true
  experiment_id: 7a996ae85ee84cd5befcf6252e7ef6d4
  hostname: 0b92e671318e
  iterations_since_restore: 2
  loss: 1.8365726371228694
  node_ip: 172.17.0.2
  pid: 1454
  should_checkpoint: true
  time_since_restore: 227.46239614486694
  time_this_iter_s: 105.0891330242157
  time_total_s: 227.46239614486694
  timestamp: 1614371394
  timesteps_since_restore: 0
  training_iteration: 2
  trial_id: da74d_00009

(pid=1415) [7,  2000] loss: 1.155
Result for DEFAULT_da74d_00007:
  accuracy: 0.4327
  date: 2021-02-26_20-29-56
  done: false
  experiment_id: f38b32d4499a4f59836f13bb7b7095f7
  hostname: 0b92e671318e
  iterations_since_restore: 2
  loss: 1.5651366052120923
  node_ip: 172.17.0.2
  pid: 1421
  should_checkpoint: true
  time_since_restore: 229.14502954483032
  time_this_iter_s: 105.93005967140198
  time_total_s: 229.14502954483032
  timestamp: 1614371396
  timesteps_since_restore: 0
  training_iteration: 2
  trial_id: da74d_00007

(pid=1419) [7,  2000] loss: 1.312
(pid=1421) [3,  2000] loss: 1.504
(pid=1415) [7,  4000] loss: 0.582
(pid=1419) [7,  4000] loss: 0.673
(pid=1421) [3,  4000] loss: 0.756
Result for DEFAULT_da74d_00008:
  accuracy: 0.573
  date: 2021-02-26_20-30-16
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 7
  loss: 1.1890086390733718
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 249.36491537094116
  time_this_iter_s: 32.48066759109497
  time_total_s: 249.36491537094116
  timestamp: 1614371416
  timesteps_since_restore: 0
  training_iteration: 7
  trial_id: da74d_00008

== Status ==
Memory usage on this node: 5.6/240.1 GiB
Using AsyncHyperBand: num_stopped=7
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 6/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.41019 |     0.5164 |                    6 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.56514 |     0.4327 |                    2 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.18901 |     0.573  |                    7 |
| DEFAULT_da74d_00001 | TERMINATED |                 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00009 | TERMINATED |                 |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


Result for DEFAULT_da74d_00000:
  accuracy: 0.4835
  date: 2021-02-26_20-30-20
  done: false
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 7
  loss: 1.4933614113330842
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 253.44921016693115
  time_this_iter_s: 33.03242492675781
  time_total_s: 253.44921016693115
  timestamp: 1614371420
  timesteps_since_restore: 0
  training_iteration: 7
  trial_id: da74d_00000

(pid=1421) [3,  6000] loss: 0.500
(pid=1415) [8,  2000] loss: 1.120
(pid=1421) [3,  8000] loss: 0.377
(pid=1419) [8,  2000] loss: 1.301
(pid=1415) [8,  4000] loss: 0.561
(pid=1421) [3, 10000] loss: 0.300
(pid=1419) [8,  4000] loss: 0.683
Result for DEFAULT_da74d_00008:
  accuracy: 0.5901
  date: 2021-02-26_20-30-48
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 8
  loss: 1.1499544531583785
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 281.1171724796295
  time_this_iter_s: 31.752257108688354
  time_total_s: 281.1171724796295
  timestamp: 1614371448
  timesteps_since_restore: 0
  training_iteration: 8
  trial_id: da74d_00008

== Status ==
Memory usage on this node: 5.8/240.1 GiB
Using AsyncHyperBand: num_stopped=7
Bracket: Iter 8.000: -1.2981835797667503 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 6/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (3 RUNNING, 7 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | RUNNING    | 172.17.0.2:1419 |            8 |   64 |  256 | 0.00646798  | 1.49336 |     0.4835 |                    7 |
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.56514 |     0.4327 |                    2 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.14995 |     0.5901 |                    8 |
| DEFAULT_da74d_00001 | TERMINATED |                 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00009 | TERMINATED |                 |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1421) [3, 12000] loss: 0.248
Result for DEFAULT_da74d_00000:
  accuracy: 0.492
  date: 2021-02-26_20-30-53
  done: true
  experiment_id: ea85a355d5fb414dbc129bd43bcddaca
  hostname: 0b92e671318e
  iterations_since_restore: 8
  loss: 1.4674230321645736
  node_ip: 172.17.0.2
  pid: 1419
  should_checkpoint: true
  time_since_restore: 286.12872838974
  time_this_iter_s: 32.67951822280884
  time_total_s: 286.12872838974
  timestamp: 1614371453
  timesteps_since_restore: 0
  training_iteration: 8
  trial_id: da74d_00000

(pid=1421) [3, 14000] loss: 0.212
(pid=1415) [9,  2000] loss: 1.077
(pid=1421) [3, 16000] loss: 0.189
(pid=1415) [9,  4000] loss: 0.554
(pid=1421) [3, 18000] loss: 0.168
Result for DEFAULT_da74d_00008:
  accuracy: 0.5745
  date: 2021-02-26_20-31-19
  done: false
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 9
  loss: 1.2056537937998772
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 312.5512430667877
  time_this_iter_s: 31.434070587158203
  time_total_s: 312.5512430667877
  timestamp: 1614371479
  timesteps_since_restore: 0
  training_iteration: 9
  trial_id: da74d_00008

== Status ==
Memory usage on this node: 5.0/240.1 GiB
Using AsyncHyperBand: num_stopped=8
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 4/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (2 RUNNING, 8 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.56514 |     0.4327 |                    2 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.20565 |     0.5745 |                    9 |
| DEFAULT_da74d_00000 | TERMINATED |                 |            8 |   64 |  256 | 0.00646798  | 1.46742 |     0.492  |                    8 |
| DEFAULT_da74d_00001 | TERMINATED |                 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00009 | TERMINATED |                 |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1421) [3, 20000] loss: 0.150
(pid=1415) [10,  2000] loss: 1.066
Result for DEFAULT_da74d_00007:
  accuracy: 0.4558
  date: 2021-02-26_20-31-35
  done: false
  experiment_id: f38b32d4499a4f59836f13bb7b7095f7
  hostname: 0b92e671318e
  iterations_since_restore: 3
  loss: 1.4805301667168735
  node_ip: 172.17.0.2
  pid: 1421
  should_checkpoint: true
  time_since_restore: 327.98270630836487
  time_this_iter_s: 98.83767676353455
  time_total_s: 327.98270630836487
  timestamp: 1614371495
  timesteps_since_restore: 0
  training_iteration: 3
  trial_id: da74d_00007

== Status ==
Memory usage on this node: 5.1/240.1 GiB
Using AsyncHyperBand: num_stopped=8
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 4/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (2 RUNNING, 8 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.48053 |     0.4558 |                    3 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.20565 |     0.5745 |                    9 |
| DEFAULT_da74d_00000 | TERMINATED |                 |            8 |   64 |  256 | 0.00646798  | 1.46742 |     0.492  |                    8 |
| DEFAULT_da74d_00001 | TERMINATED |                 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00009 | TERMINATED |                 |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1415) [10,  4000] loss: 0.539
(pid=1421) [4,  2000] loss: 1.462
Result for DEFAULT_da74d_00008:
  accuracy: 0.5935
  date: 2021-02-26_20-31-51
  done: true
  experiment_id: 647989d51d014d30b9e72cb9c54a1dc2
  hostname: 0b92e671318e
  iterations_since_restore: 10
  loss: 1.1467542746901511
  node_ip: 172.17.0.2
  pid: 1415
  should_checkpoint: true
  time_since_restore: 343.9505739212036
  time_this_iter_s: 31.399330854415894
  time_total_s: 343.9505739212036
  timestamp: 1614371511
  timesteps_since_restore: 0
  training_iteration: 10
  trial_id: da74d_00008

== Status ==
Memory usage on this node: 5.1/240.1 GiB
Using AsyncHyperBand: num_stopped=9
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5549157369375228 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 4/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (2 RUNNING, 8 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.48053 |     0.4558 |                    3 |
| DEFAULT_da74d_00008 | RUNNING    | 172.17.0.2:1415 |            8 |   32 |    8 | 0.000820594 | 1.14675 |     0.5935 |                   10 |
| DEFAULT_da74d_00000 | TERMINATED |                 |            8 |   64 |  256 | 0.00646798  | 1.46742 |     0.492  |                    8 |
| DEFAULT_da74d_00001 | TERMINATED |                 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00009 | TERMINATED |                 |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


(pid=1421) [4,  4000] loss: 0.728
(pid=1421) [4,  6000] loss: 0.493
(pid=1421) [4,  8000] loss: 0.375
(pid=1421) [4, 10000] loss: 0.298
(pid=1421) [4, 12000] loss: 0.250
(pid=1421) [4, 14000] loss: 0.206
(pid=1421) [4, 16000] loss: 0.186
(pid=1421) [4, 18000] loss: 0.166
(pid=1421) [4, 20000] loss: 0.148
Result for DEFAULT_da74d_00007:
  accuracy: 0.4495
  date: 2021-02-26_20-33-11
  done: true
  experiment_id: f38b32d4499a4f59836f13bb7b7095f7
  hostname: 0b92e671318e
  iterations_since_restore: 4
  loss: 1.5724148665212094
  node_ip: 172.17.0.2
  pid: 1421
  should_checkpoint: true
  time_since_restore: 424.4040172100067
  time_this_iter_s: 96.42131090164185
  time_total_s: 424.4040172100067
  timestamp: 1614371591
  timesteps_since_restore: 0
  training_iteration: 4
  trial_id: da74d_00007

== Status ==
Memory usage on this node: 4.3/240.1 GiB
Using AsyncHyperBand: num_stopped=10
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5724148665212094 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 2/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (1 RUNNING, 9 TERMINATED)
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc             |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00007 | RUNNING    | 172.17.0.2:1421 |            2 |    4 |   32 | 0.00104518  | 1.57241 |     0.4495 |                    4 |
| DEFAULT_da74d_00000 | TERMINATED |                 |            8 |   64 |  256 | 0.00646798  | 1.46742 |     0.492  |                    8 |
| DEFAULT_da74d_00001 | TERMINATED |                 |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |                 |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |                 |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |                 |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |                 |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |                 |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00008 | TERMINATED |                 |            8 |   32 |    8 | 0.000820594 | 1.14675 |     0.5935 |                   10 |
| DEFAULT_da74d_00009 | TERMINATED |                 |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-----------------+--------------+------+------+-------------+---------+------------+----------------------+


== Status ==
Memory usage on this node: 4.1/240.1 GiB
Using AsyncHyperBand: num_stopped=10
Bracket: Iter 8.000: -1.446412706375122 | Iter 4.000: -1.5724148665212094 | Iter 2.000: -1.653551544187963 | Iter 1.000: -1.9975281885266305
Resources requested: 0/32 CPUs, 0/2 GPUs, 0.0/157.81 GiB heap, 0.0/49.41 GiB objects (0/1.0 accelerator_type:M60)
Result logdir: /var/lib/jenkins/ray_results/DEFAULT_2021-02-26_20-26-06
Number of trials: 10/10 (10 TERMINATED)
+---------------------+------------+-------+--------------+------+------+-------------+---------+------------+----------------------+
| Trial name          | status     | loc   |   batch_size |   l1 |   l2 |          lr |    loss |   accuracy |   training_iteration |
|---------------------+------------+-------+--------------+------+------+-------------+---------+------------+----------------------|
| DEFAULT_da74d_00000 | TERMINATED |       |            8 |   64 |  256 | 0.00646798  | 1.46742 |     0.492  |                    8 |
| DEFAULT_da74d_00001 | TERMINATED |       |           16 |   64 |    8 | 0.000360487 | 1.38544 |     0.5062 |                   10 |
| DEFAULT_da74d_00002 | TERMINATED |       |            4 |   64 |   64 | 0.0142423   | 2.1816  |     0.1267 |                    1 |
| DEFAULT_da74d_00003 | TERMINATED |       |            8 |    8 |  256 | 0.0150371   | 2.07229 |     0.1835 |                    1 |
| DEFAULT_da74d_00004 | TERMINATED |       |            2 |    4 |    4 | 0.000303051 | 2.24606 |     0.1734 |                    1 |
| DEFAULT_da74d_00005 | TERMINATED |       |            8 |    8 |  128 | 0.0108518   | 1.93119 |     0.2839 |                    4 |
| DEFAULT_da74d_00006 | TERMINATED |       |            4 |    4 |    4 | 0.079216    | 2.32914 |     0.1005 |                    1 |
| DEFAULT_da74d_00007 | TERMINATED |       |            2 |    4 |   32 | 0.00104518  | 1.57241 |     0.4495 |                    4 |
| DEFAULT_da74d_00008 | TERMINATED |       |            8 |   32 |    8 | 0.000820594 | 1.14675 |     0.5935 |                   10 |
| DEFAULT_da74d_00009 | TERMINATED |       |            2 |    8 |   32 | 0.00276505  | 1.83657 |     0.334  |                    2 |
+---------------------+------------+-------+--------------+------+------+-------------+---------+------------+----------------------+


Best trial config: {'l1': 32, 'l2': 8, 'lr': 0.000820593994019208, 'batch_size': 8}
Best trial final validation loss: 1.1467542746901511
Best trial final validation accuracy: 0.5935
Files already downloaded and verified
Files already downloaded and verified
Best trial test set accuracy: 0.5993

If you run the code, an example output could look like this:

Most trials have been stopped early in order to avoid wasting resources. The best performing trial achieved a validation accuracy of about 58%, which could be confirmed on the test set.

So that’s it! You can now tune the parameters of your PyTorch models.