Deploying a MedNIST Classifier App with MONAI Deploy App SDK¶
This tutorial demos the process of packaging up a trained model using MONAI Deploy App SDK into an artifact which can be run as a local program performing inference, a workflow job doing the same, and a Docker containerized workflow execution.
In this tutorial, we will train a MedNIST classifier like the MONAI tutorial here and then implement & package the inference application, executing the application locally.
Train a MedNIST classifier model with MONAI Core¶
Setup environment¶
# Install necessary packages for MONAI Core
!python -c "import monai" || pip install -q "monai[pillow, tqdm]"
!python -c "import ignite" || pip install -q "monai[ignite]"
!python -c "import gdown" || pip install -q "monai[gdown]"
!python -c "import pydicom" || pip install -q "pydicom>=1.4.2"
!python -c "import highdicom" || pip install -q "highdicom>=0.18.2" # for the use of DICOM Writer operators
# Install MONAI Deploy App SDK package
!python -c "import monai.deploy" || pip install --upgrade -q "monai-deploy-app-sdk"
Setup imports¶
# Copyright 2020 MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import shutil
import tempfile
import glob
import PIL.Image
import torch
import numpy as np
from ignite.engine import Events
from monai.apps import download_and_extract
from monai.config import print_config
from monai.networks.nets import DenseNet121
from monai.engines import SupervisedTrainer
from monai.transforms import (
AddChannel,
Compose,
LoadImage,
RandFlip,
RandRotate,
RandZoom,
ScaleIntensity,
EnsureType,
)
from monai.utils import set_determinism
set_determinism(seed=0)
print_config()
MONAI version: 1.2.0
Numpy version: 1.24.4
Pytorch version: 2.0.1+cu117
MONAI flags: HAS_EXT = False, USE_COMPILED = False, USE_META_DICT = False
MONAI rev id: c33f1ba588ee00229a309000e888f9817b4f1934
MONAI __file__: /home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/__init__.py
Optional dependencies:
Pytorch Ignite version: 0.4.11
ITK version: NOT INSTALLED or UNKNOWN VERSION.
Nibabel version: 5.1.0
scikit-image version: 0.21.0
Pillow version: 10.0.0
Tensorboard version: NOT INSTALLED or UNKNOWN VERSION.
gdown version: 4.7.1
TorchVision version: NOT INSTALLED or UNKNOWN VERSION.
tqdm version: 4.65.0
lmdb version: NOT INSTALLED or UNKNOWN VERSION.
psutil version: 5.9.5
pandas version: NOT INSTALLED or UNKNOWN VERSION.
einops version: NOT INSTALLED or UNKNOWN VERSION.
transformers version: NOT INSTALLED or UNKNOWN VERSION.
mlflow version: NOT INSTALLED or UNKNOWN VERSION.
pynrrd version: NOT INSTALLED or UNKNOWN VERSION.
For details about installing the optional dependencies, please visit:
https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies
Download dataset¶
The MedNIST dataset was gathered from several sets from TCIA, the RSNA Bone Age Challenge(https://www.rsna.org/education/ai-resources-and-training/ai-image-challenge/rsna-pediatric-bone-age-challenge-2017), and the NIH Chest X-ray dataset.
The dataset is kindly made available by Dr. Bradley J. Erickson M.D., Ph.D. (Department of Radiology, Mayo Clinic) under the Creative Commons CC BY-SA 4.0 license.
If you use the MedNIST dataset, please acknowledge the source.
directory = os.environ.get("MONAI_DATA_DIRECTORY")
root_dir = tempfile.mkdtemp() if directory is None else directory
print(root_dir)
resource = "https://drive.google.com/uc?id=1QsnnkvZyJPcbRoV_ArW8SnE1OTuoVbKE"
md5 = "0bc7306e7427e00ad1c5526a6677552d"
compressed_file = os.path.join(root_dir, "MedNIST.tar.gz")
data_dir = os.path.join(root_dir, "MedNIST")
if not os.path.exists(data_dir):
download_and_extract(resource, compressed_file, root_dir, md5)
/tmp/tmp00iaib5g
Downloading...
From (uriginal): https://drive.google.com/uc?id=1QsnnkvZyJPcbRoV_ArW8SnE1OTuoVbKE
From (redirected): https://drive.google.com/uc?id=1QsnnkvZyJPcbRoV_ArW8SnE1OTuoVbKE&confirm=t&uuid=79a11612-ee21-4913-81f7-1db5840c71af
To: /tmp/tmpgf67zvcd/MedNIST.tar.gz
100%|██████████| 61.8M/61.8M [00:01<00:00, 58.3MB/s]
2023-07-11 12:21:48,269 - INFO - Downloaded: /tmp/tmp00iaib5g/MedNIST.tar.gz
2023-07-11 12:21:48,376 - INFO - Verified 'MedNIST.tar.gz', md5: 0bc7306e7427e00ad1c5526a6677552d.
2023-07-11 12:21:48,377 - INFO - Writing into directory: /tmp/tmp00iaib5g.
subdirs = sorted(glob.glob(f"{data_dir}/*/"))
class_names = [os.path.basename(sd[:-1]) for sd in subdirs]
image_files = [glob.glob(f"{sb}/*") for sb in subdirs]
image_files_list = sum(image_files, [])
image_class = sum(([i] * len(f) for i, f in enumerate(image_files)), [])
image_width, image_height = PIL.Image.open(image_files_list[0]).size
print(f"Label names: {class_names}")
print(f"Label counts: {list(map(len, image_files))}")
print(f"Total image count: {len(image_class)}")
print(f"Image dimensions: {image_width} x {image_height}")
Label names: ['AbdomenCT', 'BreastMRI', 'CXR', 'ChestCT', 'Hand', 'HeadCT']
Label counts: [10000, 8954, 10000, 10000, 10000, 10000]
Total image count: 58954
Image dimensions: 64 x 64
Setup and train¶
Here we’ll create a transform sequence and train the network, omitting validation and testing since we know this does indeed work and it’s not needed here:
train_transforms = Compose(
[
LoadImage(image_only=True),
AddChannel(),
ScaleIntensity(),
RandRotate(range_x=np.pi / 12, prob=0.5, keep_size=True),
RandFlip(spatial_axis=0, prob=0.5),
RandZoom(min_zoom=0.9, max_zoom=1.1, prob=0.5),
EnsureType(),
]
)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/utils/deprecate_utils.py:111: FutureWarning: <class 'monai.transforms.utility.array.AddChannel'>: Class `AddChannel` has been deprecated since version 0.8. It will be removed in version 1.3. please use MetaTensor data type and monai.transforms.EnsureChannelFirst instead with `channel_dim='no_channel'`.
warn_deprecated(obj, msg, warning_category)
class MedNISTDataset(torch.utils.data.Dataset):
def __init__(self, image_files, labels, transforms):
self.image_files = image_files
self.labels = labels
self.transforms = transforms
def __len__(self):
return len(self.image_files)
def __getitem__(self, index):
return self.transforms(self.image_files[index]), self.labels[index]
# just one dataset and loader, we won't bother with validation or testing
train_ds = MedNISTDataset(image_files_list, image_class, train_transforms)
train_loader = torch.utils.data.DataLoader(train_ds, batch_size=300, shuffle=True, num_workers=10)
device = torch.device("cuda:0")
net = DenseNet121(spatial_dims=2, in_channels=1, out_channels=len(class_names)).to(device)
loss_function = torch.nn.CrossEntropyLoss()
opt = torch.optim.Adam(net.parameters(), 1e-5)
max_epochs = 5
def _prepare_batch(batch, device, non_blocking):
return tuple(b.to(device) for b in batch)
trainer = SupervisedTrainer(device, max_epochs, train_loader, net, opt, loss_function, prepare_batch=_prepare_batch)
@trainer.on(Events.EPOCH_COMPLETED)
def _print_loss(engine):
print(f"Epoch {engine.state.epoch}/{engine.state.max_epochs} Loss: {engine.state.output[0]['loss']}")
trainer.run()
Epoch 1/5 Loss: 0.18928290903568268
Epoch 2/5 Loss: 0.06710730493068695
Epoch 3/5 Loss: 0.029032323509454727
Epoch 4/5 Loss: 0.01877668686211109
Epoch 5/5 Loss: 0.01939055137336254
The network will be saved out here as a Torchscript object named classifier.zip
torch.jit.script(net).save("classifier.zip")
Implementing and Packaging Application with MONAI Deploy App SDK¶
Based on the Torchscript model(classifier.zip), we will implement an application that process an input Jpeg image and write the prediction(classification) result as JSON file(output.json).
Creating Operators and connecting them in Application class¶
We used the following train transforms as pre-transforms during the training.
Train transforms used in training¶
1train_transforms = Compose(
2 [
3 LoadImage(image_only=True),
4 AddChannel(),
5 ScaleIntensity(),
6 RandRotate(range_x=np.pi / 12, prob=0.5, keep_size=True),
7 RandFlip(spatial_axis=0, prob=0.5),
8 RandZoom(min_zoom=0.9, max_zoom=1.1, prob=0.5),
9 EnsureType(),
10 ]
11)
RandRotate, RandFlip, and RandZoom transforms are used only for training and those are not necessary during the inference.
In our inference application, we will define two operators:
LoadPILOperator- Load a JPEG image from the input path and pass the loaded image object to the next operator.MedNISTClassifierOperator- Pre-transform the given image by using MONAI’sComposeclass, feed to the Torchscript model (classifier.zip), and write the prediction into JSON file(output.json)
The workflow of the application would look like this.
%%{init: {"theme": "base", "themeVariables": { "fontSize": "16px"}} }%%
classDiagram
direction LR
LoadPILOperator --|> MedNISTClassifierOperator : image...image
class LoadPILOperator {
<in>image : DISK
image(out) IN_MEMORY
}
class MedNISTClassifierOperator {
<in>image : IN_MEMORY
output(out) DISK
}
Setup imports¶
Let’s import necessary classes/decorators and define MEDNIST_CLASSES.
import monai.deploy.core as md # 'md' stands for MONAI Deploy (or can use 'core' instead)
from monai.deploy.core import (
Application,
DataPath,
ExecutionContext,
Image,
InputContext,
IOType,
Operator,
OutputContext,
)
from monai.transforms import AddChannel, Compose, EnsureType, ScaleIntensity
MEDNIST_CLASSES = ["AbdomenCT", "BreastMRI", "CXR", "ChestCT", "Hand", "HeadCT"]
Creating Operator classes¶
LoadPILOperator¶
@md.input("image", DataPath, IOType.DISK)
@md.output("image", Image, IOType.IN_MEMORY)
@md.env(pip_packages=["pillow"])
class LoadPILOperator(Operator):
"""Load image from the given input (DataPath) and set numpy array to the output (Image)."""
def compute(self, op_input: InputContext, op_output: OutputContext, context: ExecutionContext):
import numpy as np
from PIL import Image as PILImage
input_path = op_input.get().path
if input_path.is_dir():
input_path = next(input_path.glob("*.*")) # take the first file
image = PILImage.open(input_path)
image = image.convert("L") # convert to greyscale image
image_arr = np.asarray(image)
output_image = Image(image_arr) # create Image domain object with a numpy array
op_output.set(output_image)
MedNISTClassifierOperator¶
@md.input("image", Image, IOType.IN_MEMORY)
@md.output("output", DataPath, IOType.DISK)
@md.env(pip_packages=["monai"])
class MedNISTClassifierOperator(Operator):
"""Classifies the given image and returns the class name."""
@property
def transform(self):
return Compose([AddChannel(), ScaleIntensity(), EnsureType()])
def compute(self, op_input: InputContext, op_output: OutputContext, context: ExecutionContext):
import json
import torch
img = op_input.get().asnumpy() # (64, 64), uint8
image_tensor = self.transform(img) # (1, 64, 64), torch.float64
image_tensor = image_tensor[None].float() # (1, 1, 64, 64), torch.float32
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
image_tensor = image_tensor.to(device)
model = context.models.get() # get a TorchScriptModel object
with torch.no_grad():
outputs = model(image_tensor)
_, output_classes = outputs.max(dim=1)
result = MEDNIST_CLASSES[output_classes[0]] # get the class name
print(result)
# Get output (folder) path and create the folder if not exists
output_folder = op_output.get().path
output_folder.mkdir(parents=True, exist_ok=True)
# Write result to "output.json"
output_path = output_folder / "output.json"
with open(output_path, "w") as fp:
json.dump(result, fp)
Creating Application class¶
Our application class would look like below.
It defines App class inheriting Application class.
LoadPILOperator is connected to MedNISTClassifierOperator by using self.add_flow() in compose() method of App.
@md.resource(cpu=1, gpu=1, memory="1Gi")
@md.env(pip_packages=["pydicom >= 2.3.0", "highdicom>=0.18.2"]) # for the use of DICOM Writer operators
class App(Application):
"""Application class for the MedNIST classifier."""
def compose(self):
load_pil_op = LoadPILOperator()
classifier_op = MedNISTClassifierOperator()
self.add_flow(load_pil_op, classifier_op)
Executing app locally¶
Let’s find a test input file path to use.
test_input_path = image_files[0][0]
print(f"Test input file path: {test_input_path}")
Test input file path: /tmp/tmp00iaib5g/MedNIST/AbdomenCT/001420.jpeg
We can execute the app in the Jupyter notebook.
app = App()
app.run(input=test_input_path, output="output", model="classifier.zip")
Going to initiate execution of operator LoadPILOperator
Executing operator LoadPILOperator (Process ID: 393049, Operator ID: c60f371c-73bc-4bb7-aaa6-30d04f2ff280)
Done performing execution of operator LoadPILOperator
Going to initiate execution of operator MedNISTClassifierOperator
Executing operator MedNISTClassifierOperator (Process ID: 393049, Operator ID: 6e94713f-4e1d-4ec4-ae69-8305e8b02b7f)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/utils/deprecate_utils.py:111: FutureWarning: <class 'monai.transforms.utility.array.AddChannel'>: Class `AddChannel` has been deprecated since version 0.8. It will be removed in version 1.3. please use MetaTensor data type and monai.transforms.EnsureChannelFirst instead with `channel_dim='no_channel'`.
warn_deprecated(obj, msg, warning_category)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/data/meta_tensor.py:116: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:206.)
return torch.as_tensor(x, *args, **_kwargs).as_subclass(cls) # type: ignore
AbdomenCT
Done performing execution of operator MedNISTClassifierOperator
!cat output/output.json
"AbdomenCT"
Once the application is verified inside Jupyter notebook, we can write the whole application as a file(mednist_classifier_monaideploy.py) by concatenating code above, then add the following lines:
if __name__ == "__main__":
App(do_run=True)
The above lines are needed to execute the application code by using python interpreter.
%%writefile mednist_classifier_monaideploy.py
# Copyright 2021 MONAI Consortium
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import monai.deploy.core as md # 'md' stands for MONAI Deploy (or can use 'core' instead)
from monai.deploy.core import (
Application,
DataPath,
ExecutionContext,
Image,
InputContext,
IOType,
Operator,
OutputContext,
)
from monai.transforms import AddChannel, Compose, EnsureType, ScaleIntensity
MEDNIST_CLASSES = ["AbdomenCT", "BreastMRI", "CXR", "ChestCT", "Hand", "HeadCT"]
@md.input("image", DataPath, IOType.DISK)
@md.output("image", Image, IOType.IN_MEMORY)
@md.env(pip_packages=["pillow"])
class LoadPILOperator(Operator):
"""Load image from the given input (DataPath) and set numpy array to the output (Image)."""
def compute(self, op_input: InputContext, op_output: OutputContext, context: ExecutionContext):
import numpy as np
from PIL import Image as PILImage
input_path = op_input.get().path
if input_path.is_dir():
input_path = next(input_path.glob("*.*")) # take the first file
image = PILImage.open(input_path)
image = image.convert("L") # convert to greyscale image
image_arr = np.asarray(image)
output_image = Image(image_arr) # create Image domain object with a numpy array
op_output.set(output_image)
@md.input("image", Image, IOType.IN_MEMORY)
@md.output("output", DataPath, IOType.DISK)
@md.env(pip_packages=["monai"])
class MedNISTClassifierOperator(Operator):
"""Classifies the given image and returns the class name."""
@property
def transform(self):
return Compose([AddChannel(), ScaleIntensity(), EnsureType()])
def compute(self, op_input: InputContext, op_output: OutputContext, context: ExecutionContext):
import json
import torch
img = op_input.get().asnumpy() # (64, 64), uint8
image_tensor = self.transform(img) # (1, 64, 64), torch.float64
image_tensor = image_tensor[None].float() # (1, 1, 64, 64), torch.float32
device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
image_tensor = image_tensor.to(device)
model = context.models.get() # get a TorchScriptModel object
with torch.no_grad():
outputs = model(image_tensor)
_, output_classes = outputs.max(dim=1)
result = MEDNIST_CLASSES[output_classes[0]] # get the class name
print(result)
# Get output (folder) path and create the folder if not exists
output_folder = op_output.get().path
output_folder.mkdir(parents=True, exist_ok=True)
# Write result to "output.json"
output_path = output_folder / "output.json"
with open(output_path, "w") as fp:
json.dump(result, fp)
@md.resource(cpu=1, gpu=1, memory="1Gi")
@md.env(pip_packages=["pydicom >= 2.3.0", "highdicom>=0.18.2"]) # for the use of DICOM Writer operators
class App(Application):
"""Application class for the MedNIST classifier."""
def compose(self):
load_pil_op = LoadPILOperator()
classifier_op = MedNISTClassifierOperator()
self.add_flow(load_pil_op, classifier_op)
if __name__ == "__main__":
App(do_run=True)
Overwriting mednist_classifier_monaideploy.py
In this time, let’s execute the app in the command line.
!python mednist_classifier_monaideploy.py -i {test_input_path} -o output -m classifier.zip
Going to initiate execution of operator LoadPILOperator
Executing operator LoadPILOperator (Process ID: 394647, Operator ID: 9502cae2-e14b-4c3f-be35-57dc9289ea89)
Done performing execution of operator LoadPILOperator
Going to initiate execution of operator MedNISTClassifierOperator
Executing operator MedNISTClassifierOperator (Process ID: 394647, Operator ID: 66c5dc76-5e54-4a46-9a23-c0c6a70f36af)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/utils/deprecate_utils.py:111: FutureWarning: <class 'monai.transforms.utility.array.AddChannel'>: Class `AddChannel` has been deprecated since version 0.8. It will be removed in version 1.3. please use MetaTensor data type and monai.transforms.EnsureChannelFirst instead with `channel_dim='no_channel'`.
warn_deprecated(obj, msg, warning_category)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/data/meta_tensor.py:116: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:206.)
return torch.as_tensor(x, *args, **_kwargs).as_subclass(cls) # type: ignore
AbdomenCT
Done performing execution of operator MedNISTClassifierOperator
Above command is same with the following command line:
!monai-deploy exec mednist_classifier_monaideploy.py -i {test_input_path} -o output -m classifier.zip
Going to initiate execution of operator LoadPILOperator
Executing operator LoadPILOperator (Process ID: 394701, Operator ID: c0d3561c-6274-4953-a642-8265c6a65bc9)
Done performing execution of operator LoadPILOperator
Going to initiate execution of operator MedNISTClassifierOperator
Executing operator MedNISTClassifierOperator (Process ID: 394701, Operator ID: 77db8991-6777-4c06-b28f-670b856193e4)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/utils/deprecate_utils.py:111: FutureWarning: <class 'monai.transforms.utility.array.AddChannel'>: Class `AddChannel` has been deprecated since version 0.8. It will be removed in version 1.3. please use MetaTensor data type and monai.transforms.EnsureChannelFirst instead with `channel_dim='no_channel'`.
warn_deprecated(obj, msg, warning_category)
/home/mqin/src/monai-deploy-app-sdk/.venv05/lib/python3.8/site-packages/monai/data/meta_tensor.py:116: UserWarning: The given NumPy array is not writable, and PyTorch does not support non-writable tensors. This means writing to this tensor will result in undefined behavior. You may want to copy the array to protect its data or make it writable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at ../torch/csrc/utils/tensor_numpy.cpp:206.)
return torch.as_tensor(x, *args, **_kwargs).as_subclass(cls) # type: ignore
AbdomenCT
Done performing execution of operator MedNISTClassifierOperator
!cat output/output.json
"AbdomenCT"
Packaging app¶
Let’s package the app with MONAI Application Packager.
!monai-deploy package mednist_classifier_monaideploy.py --tag mednist_app:latest --model classifier.zip # -l DEBUG
Building MONAI Application Package... -?25l[+] Building 0.0s (0/1)
?25\?25l[+] Building 0.1s (4/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.1s
=> => transferring context: 23B 0.1s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
?25h?25l[+] Building 0.3s (4/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
?25|?25l[+] Building 0.4s (9/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.1s
?25/?25l[+] Building 0.5s (10/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
?25h?25l[+] Building 0.7s (11/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.1s
?25-?25l[+] Building 0.8s (11/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.3s
?25\?25l[+] Building 1.0s (11/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.4s
=> => # % Total % Received % Xferd Average Speed Time Time Time
=> => # Current
=> => # Dload Upload Total Spent Left
=> => # Speed
=> => # 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:
=> => # -- 0
?25h?25l[+] Building 1.1s (11/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.5s
=> => # Current
=> => # Dload Upload Total Spent Left
=> => # Speed
=> => # 0 0 0 0 0 0 0 0 --:--:-- --:--:-- --:--:
=> => # 100 11.9M 100 11.9M 0 0 59.0M 0 --:--:-- --:--:-- --:--:
=> => # -- 59.0M
?25|?25l[+] Building 1.3s (11/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.7s
=> => # Archive: /opt/monai/executor/executor.zip
=> => # inflating: /opt/monai/executor/executor_pkg/_rels/.rels
=> => # inflating: /opt/monai/executor/executor_pkg/Monai.Deploy.Executor.nu
=> => # spec
=> => # inflating: /opt/monai/executor/executor_pkg/lib/native/linux-x64/mon
=> => # ai-exec
?25/?25l[+] Building 1.4s (11/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.8s
=> => # inflating: /opt/monai/executor/executor_pkg/lib/native/linux-x64/mon
=> => # ai-exec
=> => # inflating: /opt/monai/executor/executor_pkg/[Content_Types].xml
=> => # inflating: /opt/monai/executor/executor_pkg/package/services/metadat
=> => # a/core-properties/c09c14c8557342a7b41ac545107c1263.psmdcp
=> => # extracting: /opt/monai/executor/executor_pkg/.signature.p7s
?25-?25l[+] Building 1.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 0.1s
?25h?25l[+] Building 1.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 0.2s
?25\?25l[+] Building 1.9s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 0.4s
?25|?25l[+] Building 2.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 0.5s
?25/?25l[+] Building 2.2s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 0.7s
?25h?25l[+] Building 2.3s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 0.8s
?25-?25l[+] Building 2.5s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.0s
=> => # Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.c
=> => # om
?25\?25l[+] Building 2.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.1s
=> => # Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.c
=> => # om
?25h?25l[+] Building 2.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.3s
=> => # Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.c
=> => # om
=> => # Collecting pydicom>=2.3.0
=> => # Downloading pydicom-2.4.1-py3-none-any.whl (1.8 MB)
?25|?25l[+] Building 2.9s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.4s
=> => # Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.c
=> => # om
=> => # Collecting pydicom>=2.3.0
=> => # Downloading pydicom-2.4.1-py3-none-any.whl (1.8 MB)
=> => # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.8/1.8 MB 25.5 MB/s eta
=> => # 0:00:00
?25/?25l[+] Building 3.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.6s
=> => # Looking in indexes: https://pypi.org/simple, https://pypi.ngc.nvidia.c
=> => # om
=> => # Collecting pydicom>=2.3.0
=> => # Downloading pydicom-2.4.1-py3-none-any.whl (1.8 MB)
=> => # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.8/1.8 MB 25.5 MB/s eta
=> => # 0:00:00
?25h?25l[+] Building 3.1s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.7s
=> => # Collecting pydicom>=2.3.0
=> => # Downloading pydicom-2.4.1-py3-none-any.whl (1.8 MB)
=> => # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 1.8/1.8 MB 25.5 MB/s eta
=> => # 0:00:00
=> => # Collecting highdicom>=0.18.2
=> => # Downloading highdicom-0.21.1-py3-none-any.whl (807 kB)
?25-?25l[+] Building 3.3s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 1.8s
=> => # Collecting highdicom>=0.18.2
=> => # Downloading highdicom-0.21.1-py3-none-any.whl (807 kB)
=> => # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 807.1/807.1 kB 15.6 MB/s e
=> => # ta 0:00:00
=> => # Requirement already satisfied: pillow in /opt/conda/lib/python3.8/site
=> => # -packages (from -r /opt/monai/app/requirements.txt (line 3)) (9.0.1)
?25\?25l[+] Building 3.4s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.0s
=> => # Collecting highdicom>=0.18.2
=> => # Downloading highdicom-0.21.1-py3-none-any.whl (807 kB)
=> => # ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 807.1/807.1 kB 15.6 MB/s e
=> => # ta 0:00:00
=> => # Requirement already satisfied: pillow in /opt/conda/lib/python3.8/site
=> => # -packages (from -r /opt/monai/app/requirements.txt (line 3)) (9.0.1)
?25|?25l[+] Building 3.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.1s
=> => # Requirement already satisfied: networkx>=2.4 in /opt/conda/lib/python3
=> => # .8/site-packages (from -r /opt/monai/app/requirements.txt (line 6)) (2
=> => # .6.3)
=> => # Requirement already satisfied: colorama>=0.4.1 in /opt/conda/lib/pytho
=> => # n3.8/site-packages (from -r /opt/monai/app/requirements.txt (line 7))
=> => # (0.4.5)
?25h?25l[+] Building 3.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.2s
=> => # .8/site-packages (from -r /opt/monai/app/requirements.txt (line 6)) (2
=> => # .6.3)
=> => # Requirement already satisfied: colorama>=0.4.1 in /opt/conda/lib/pytho
=> => # n3.8/site-packages (from -r /opt/monai/app/requirements.txt (line 7))
=> => # (0.4.5)
=> => # Collecting typeguard>=3.0.0
?25/?25l[+] Building 3.9s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.4s
=> => # .6.3)
=> => # Requirement already satisfied: colorama>=0.4.1 in /opt/conda/lib/pytho
=> => # n3.8/site-packages (from -r /opt/monai/app/requirements.txt (line 7))
=> => # (0.4.5)
=> => # Collecting typeguard>=3.0.0
=> => # Downloading typeguard-4.0.0-py3-none-any.whl (33 kB)
?25-?25l[+] Building 4.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.5s
=> => # Requirement already satisfied: colorama>=0.4.1 in /opt/conda/lib/pytho
=> => # n3.8/site-packages (from -r /opt/monai/app/requirements.txt (line 7))
=> => # (0.4.5)
=> => # Collecting typeguard>=3.0.0
=> => # Downloading typeguard-4.0.0-py3-none-any.whl (33 kB)
=> => # Collecting pillow-jpls>=1.0
?25h?25l[+] Building 4.1s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.6s
=> => # Requirement already satisfied: torch>=1.9 in /opt/conda/lib/python3.8/
=> => # site-packages (from monai->-r /opt/monai/app/requirements.txt (line 4)
=> => # ) (1.13.0a0+d321be6)
=> => # Requirement already satisfied: importlib-metadata>=3.6 in /opt/conda/l
=> => # ib/python3.8/site-packages (from typeguard>=3.0.0->-r /opt/monai/app/r
=> => # equirements.txt (line 8)) (4.12.0)
?25\?25l[+] Building 4.3s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.8s
=> => # Requirement already satisfied: torch>=1.9 in /opt/conda/lib/python3.8/
=> => # site-packages (from monai->-r /opt/monai/app/requirements.txt (line 4)
=> => # ) (1.13.0a0+d321be6)
=> => # Requirement already satisfied: importlib-metadata>=3.6 in /opt/conda/l
=> => # ib/python3.8/site-packages (from typeguard>=3.0.0->-r /opt/monai/app/r
=> => # equirements.txt (line 8)) (4.12.0)
?25|?25l[+] Building 4.4s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 2.9s
=> => # equirements.txt (line 8)) (4.12.0)
=> => # Collecting typing-extensions>=4.4.0
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
?25/?25l[+] Building 4.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 3.1s
=> => # equirements.txt (line 8)) (4.12.0)
=> => # Collecting typing-extensions>=4.4.0
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
?25h?25l[+] Building 4.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 3.2s
=> => # equirements.txt (line 8)) (4.12.0)
=> => # Collecting typing-extensions>=4.4.0
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
?25-?25l[+] Building 4.9s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 3.4s
=> => # equirements.txt (line 8)) (4.12.0)
=> => # Collecting typing-extensions>=4.4.0
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
?25\?25l[+] Building 5.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 3.5s
=> => # equirements.txt (line 8)) (4.12.0)
=> => # Collecting typing-extensions>=4.4.0
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
?25|?25l[+] Building 5.2s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 3.7s
=> => # equirements.txt (line 8)) (4.12.0)
=> => # Collecting typing-extensions>=4.4.0
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
?25h?25l[+] Building 5.3s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 3.8s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25/?25l[+] Building 5.4s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.0s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25-?25l[+] Building 5.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.1s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25h?25l[+] Building 5.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.3s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25\?25l[+] Building 5.9s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.4s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25|?25l[+] Building 6.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.6s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25/?25l[+] Building 6.2s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.7s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25h?25l[+] Building 6.3s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 4.9s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25-?25l[+] Building 6.5s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.0s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25\?25l[+] Building 6.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.2s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25|?25l[+] Building 6.8s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.3s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25h?25l[+] Building 6.9s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.5s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25/?25l[+] Building 7.1s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.6s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25-?25l[+] Building 7.2s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.8s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25\?25l[+] Building 7.4s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 5.9s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25h?25l[+] Building 7.5s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.1s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25|?25l[+] Building 7.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.2s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25/?25l[+] Building 7.8s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.4s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25-?25l[+] Building 8.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.5s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25h?25l[+] Building 8.1s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.7s
=> => # Downloading typing_extensions-4.7.1-py3-none-any.whl (33 kB)
=> => # Requirement already satisfied: zipp>=0.5 in /opt/conda/lib/python3.8/s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
?25\?25l[+] Building 8.3s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.8s
=> => # ite-packages (from importlib-metadata>=3.6->typeguard>=3.0.0->-r /opt/
=> => # monai/app/requirements.txt (line 8)) (3.8.1)
=> => # Installing collected packages: typing-extensions, pydicom, pillow-jpls
=> => # , typeguard, highdicom, monai
=> => # Successfully installed highdicom-0.21.1 monai-1.2.0 pillow-jpls-1.2.0
=> => # pydicom-2.4.1 typeguard-4.0.0 typing-extensions-4.7.1
?25|?25l[+] Building 8.4s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 6.9s
=> => # Successfully installed highdicom-0.21.1 monai-1.2.0 pillow-jpls-1.2.0
=> => # pydicom-2.4.1 typeguard-4.0.0 typing-extensions-4.7.1
=> => # WARNING: Running pip as the 'root' user can result in broken permissio
=> => # ns and conflicting behaviour with the system package manager. It is re
=> => # commended to use a virtual environment instead: https://pip.pypa.io/wa
=> => # rnings/venv
?25/?25l[+] Building 8.6s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.1s
=> => # Successfully installed highdicom-0.21.1 monai-1.2.0 pillow-jpls-1.2.0
=> => # pydicom-2.4.1 typeguard-4.0.0 typing-extensions-4.7.1
=> => # WARNING: Running pip as the 'root' user can result in broken permissio
=> => # ns and conflicting behaviour with the system package manager. It is re
=> => # commended to use a virtual environment instead: https://pip.pypa.io/wa
=> => # rnings/venv
?25h?25l[+] Building 8.7s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.2s
=> => # WARNING: Running pip as the 'root' user can result in broken permissio
=> => # ns and conflicting behaviour with the system package manager. It is re
=> => # commended to use a virtual environment instead: https://pip.pypa.io/wa
=> => # rnings/venv
=> => # [notice] A new release of pip available: 22.3 -> 23.1.2
=> => # [notice] To update, run: pip install --upgrade pip
?25-?25l[+] Building 8.8s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.4s
=> => # WARNING: Running pip as the 'root' user can result in broken permissio
=> => # ns and conflicting behaviour with the system package manager. It is re
=> => # commended to use a virtual environment instead: https://pip.pypa.io/wa
=> => # rnings/venv
=> => # [notice] A new release of pip available: 22.3 -> 23.1.2
=> => # [notice] To update, run: pip install --upgrade pip
?25\?25l[+] Building 9.0s (12/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> => # WARNING: Running pip as the 'root' user can result in broken permissio
=> => # ns and conflicting behaviour with the system package manager. It is re
=> => # commended to use a virtual environment instead: https://pip.pypa.io/wa
=> => # rnings/venv
=> => # [notice] A new release of pip available: 22.3 -> 23.1.2
=> => # [notice] To update, run: pip install --upgrade pip
?25h?25l[+] Building 9.1s (14/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.1s
?25|?25l[+] Building 9.3s (14/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.2s
?25/?25l[+] Building 9.4s (14/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.4s
?25-?25l[+] Building 9.6s (14/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> => # User site package location: /root/.local/lib/python3.8/site-packages
?25h?25l[+] Building 9.7s (17/19)
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> [12/15] COPY ./map/app.json /etc/monai/ 0.0s
=> [13/15] COPY ./map/pkg.json /etc/monai/ 0.0s
=> [14/15] COPY ./app /opt/monai/app 0.0s
?25\?25l[+] Building 9.8s (19/20)
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> [12/15] COPY ./map/app.json /etc/monai/ 0.0s
=> [13/15] COPY ./map/pkg.json /etc/monai/ 0.0s
=> [14/15] COPY ./app /opt/monai/app 0.0s
=> [15/15] WORKDIR /var/monai/ 0.0s
=> exporting to image 0.1s
=> => exporting layers 0.1s
?25|?25l[+] Building 10.0s (19/20)
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> [12/15] COPY ./map/app.json /etc/monai/ 0.0s
=> [13/15] COPY ./map/pkg.json /etc/monai/ 0.0s
=> [14/15] COPY ./app /opt/monai/app 0.0s
=> [15/15] WORKDIR /var/monai/ 0.0s
=> exporting to image 0.2s
=> => exporting layers 0.2s
?25h?25l[+] Building 10.1s (19/20)
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> [12/15] COPY ./map/app.json /etc/monai/ 0.0s
=> [13/15] COPY ./map/pkg.json /etc/monai/ 0.0s
=> [14/15] COPY ./app /opt/monai/app 0.0s
=> [15/15] WORKDIR /var/monai/ 0.0s
=> exporting to image 0.4s
=> => exporting layers 0.4s
?25/?25l[+] Building 10.3s (19/20)
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> [12/15] COPY ./map/app.json /etc/monai/ 0.0s
=> [13/15] COPY ./map/pkg.json /etc/monai/ 0.0s
=> [14/15] COPY ./app /opt/monai/app 0.0s
=> [15/15] WORKDIR /var/monai/ 0.0s
=> exporting to image 0.5s
=> => exporting layers 0.5s
?25-?25l[+] Building 10.4s (20/20) FINISHED
=> [internal] load build definition from dockerfile 0.0s
=> => transferring dockerfile: 2.58kB 0.0s
=> [internal] load .dockerignore 0.0s
=> => transferring context: 1.11kB 0.0s
=> [internal] load metadata for nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> [internal] load build context 0.2s
=> => transferring context: 29.08MB 0.2s
=> [ 1/15] FROM nvcr.io/nvidia/pytorch:22.08-py3 0.0s
=> CACHED [ 2/15] RUN apt update && apt upgrade -y --no-install-rec 0.0s
=> CACHED [ 3/15] RUN pip install --no-cache-dir --upgrade setuptools==5 0.0s
=> CACHED [ 4/15] RUN mkdir -p /etc/monai/ && mkdir -p /opt/monai/ 0.0s
=> CACHED [ 5/15] RUN mkdir -p /opt/monai/models 0.0s
=> [ 6/15] COPY ./models /opt/monai/models 0.2s
=> [ 7/15] COPY ./pip/requirements.txt /opt/monai/app/requirements.txt 0.0s
=> [ 8/15] RUN curl https://globalcdn.nuget.org/packages/monai.deploy.ex 0.9s
=> [ 9/15] RUN pip install --no-cache-dir --user -r /opt/monai/app/requi 7.5s
=> [10/15] COPY ./monai-deploy-app-sdk /root/.local/lib/python3.8/site-p 0.1s
=> [11/15] RUN echo "User site package location: $(python3 -m site --use 0.5s
=> [12/15] COPY ./map/app.json /etc/monai/ 0.0s
=> [13/15] COPY ./map/pkg.json /etc/monai/ 0.0s
=> [14/15] COPY ./app /opt/monai/app 0.0s
=> [15/15] WORKDIR /var/monai/ 0.0s
=> exporting to image 0.6s
=> => exporting layers 0.6s
=> => writing image sha256:1eba359ad2aef41161eb2253c8ddaf172acc72bc3eaa5 0.0s
=> => naming to docker.io/library/mednist_app:latest 0.0s
?25Done
[2023-07-11 12:29:09,060] [INFO] (app_packager) - Successfully built mednist_app:latest
Note
Building a MONAI Application Package (Docker image) can take time. Use -l DEBUG option if you want to see the progress.
We can see that the Docker image is created.
!docker image ls | grep mednist_app
mednist_app latest 1eba359ad2ae 3 seconds ago 15GB
Executing packaged app locally¶
The packaged app can be run locally through MONAI Application Runner.
# Copy a test input file to 'input' folder
!mkdir -p input && rm -rf input/*
!echo "Test Input Path: " {test_input_path}
!cp {test_input_path} input/
!echo "MAP input folder files:"
!ls input
# Launch the app
!monai-deploy run mednist_app:latest input output
Test Input Path: /tmp/tmp00iaib5g/MedNIST/AbdomenCT/001420.jpeg
MAP input folder files:
001420.jpeg
Checking dependencies...
--> Verifying if "docker" is installed...
--> Verifying if "mednist_app:latest" is available...
Checking for MAP "mednist_app:latest" locally
"mednist_app:latest" found.
Reading MONAI App Package manifest...
Preparing to copy...?25lCopying from container - 0B?25hSuccessfully copied 2.05kB to /tmp/tmp0_zu2d_p/app.json
Preparing to copy...?25lCopying from container - 0B?25hSuccessfully copied 2.05kB to /tmp/tmp0_zu2d_p/pkg.json
--> Verifying if "nvidia-docker" is installed...
/opt/conda/lib/python3.8/site-packages/scipy/__init__.py:138: UserWarning: A NumPy version >=1.16.5 and <1.23.0 is required for this version of SciPy (detected version 1.24.3)
warnings.warn(f"A NumPy version >={np_minversion} and <{np_maxversion} is required for this version of "
Going to initiate execution of operator LoadPILOperator
Executing operator LoadPILOperator (Process ID: 1, Operator ID: ffdb9a34-3aab-42c7-b850-1e807d4abc42)
Done performing execution of operator LoadPILOperator
Going to initiate execution of operator MedNISTClassifierOperator
Executing operator MedNISTClassifierOperator (Process ID: 1, Operator ID: 0ed76555-578f-4b9e-8d41-4629eca56630)
/root/.local/lib/python3.8/site-packages/monai/utils/deprecate_utils.py:111: FutureWarning: <class 'monai.transforms.utility.array.AddChannel'>: Class `AddChannel` has been deprecated since version 0.8. It will be removed in version 1.3. please use MetaTensor data type and monai.transforms.EnsureChannelFirst instead with `channel_dim='no_channel'`.
warn_deprecated(obj, msg, warning_category)
AbdomenCT
Done performing execution of operator MedNISTClassifierOperator
!cat output/output.json
"AbdomenCT"
Note: Please execute the following script once the exercise is done.
# Remove data files which is in the temporary folder
if directory is None:
shutil.rmtree(root_dir)