change: add MXNet 1.4.1 support#886

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laurenyu merged 7 commits into from
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change: add MXNet 1.4.1 support #886

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5c05ec4
update docs
laurenyu Jun 24, 2019
435819d
update pytest fixture
laurenyu Jun 24, 2019
e214ae4
bump LATEST_VERSION
laurenyu Jul 3, 2019
00011ec
Merge branch 'master' into mx-1.4.1
laurenyu Jul 3, 2019
a02e488
Merge branch 'master' into mx-1.4.1
laurenyu Jul 3, 2019
715e202
Merge branch 'master' into mx-1.4.1
laurenyu Jul 18, 2019
7352f5f
Merge branch 'master' into mx-1.4.1
laurenyu Jul 18, 2019
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4 changes: 2 additions & 2 deletions README.rst
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Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down
32 changes: 16 additions & 16 deletions doc/using_mxnet.rst
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Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down
32 changes: 16 additions & 16 deletions src/sagemaker/mxnet/README.rst
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Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down
2 changes: 1 addition & 1 deletion src/sagemaker/mxnet/estimator.py
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Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
__framework_name__ = "mxnet"
_LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

LATEST_VERSION = "1.4"
LATEST_VERSION = "1.4.1"
"""The latest version of MXNet included in the SageMaker pre-built Docker images."""

def __init__(
Expand Down
1 change: 1 addition & 0 deletions tests/conftest.py
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Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
"1.3.0",
"1.4",
"1.4.0",
"1.4.1",
],
)
def mxnet_version(request):
Expand Down
, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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change: add MXNet 1.4.1 support#886

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to your account

 Merged

laurenyu
merged 7 commits into

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Jul 18, 2019
 Merged


change: add MXNet 1.4.1 support
#886
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5c05ec4

update docs


laurenyu Jun 24, 2019
435819d

update pytest fixture


laurenyu Jun 24, 2019
e214ae4

bump LATEST_VERSION


laurenyu Jul 3, 2019
00011ec

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
a02e488

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
715e202

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019
7352f5f

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019

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4 changes: 2 additions & 2 deletions
README.rst

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Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
Expand Down

1 change: 1 addition & 0 deletions
tests/conftest.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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#886
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update docs


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update pytest fixture


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e214ae4

bump LATEST_VERSION


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Merge branch 'master' into mx-1.4.1


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Merge branch 'master' into mx-1.4.1


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4 changes: 2 additions & 2 deletions
README.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
Expand Down

1 change: 1 addition & 0 deletions
tests/conftest.py

View file


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Original file line numberDiff line numberDiff line change
Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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change: add MXNet 1.4.1 support#886

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 Merged

laurenyu
merged 7 commits into

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Jul 18, 2019
 Merged


change: add MXNet 1.4.1 support
#886
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5c05ec4

update docs


laurenyu Jun 24, 2019
435819d

update pytest fixture


laurenyu Jun 24, 2019
e214ae4

bump LATEST_VERSION


laurenyu Jul 3, 2019
00011ec

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
a02e488

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
715e202

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019
7352f5f

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019

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4 changes: 2 additions & 2 deletions
README.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
Expand Down

1 change: 1 addition & 0 deletions
tests/conftest.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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change: add MXNet 1.4.1 support#886

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change: add MXNet 1.4.1 support
#886
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update docs


laurenyu Jun 24, 2019
435819d

update pytest fixture


laurenyu Jun 24, 2019
e214ae4

bump LATEST_VERSION


laurenyu Jul 3, 2019
00011ec

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
a02e488

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
715e202

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019
7352f5f

Merge branch 'master' into mx-1.4.1


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4 changes: 2 additions & 2 deletions
README.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
Expand Down

1 change: 1 addition & 0 deletions
tests/conftest.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
change: add MXNet 1.4.1 support#886

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Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

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 Merged

laurenyu
merged 7 commits into

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Jul 18, 2019
 Merged


change: add MXNet 1.4.1 support
#886
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5c05ec4

update docs


laurenyu Jun 24, 2019
435819d

update pytest fixture


laurenyu Jun 24, 2019
e214ae4

bump LATEST_VERSION


laurenyu Jul 3, 2019
00011ec

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
a02e488

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
715e202

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019
7352f5f

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019

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4 changes: 2 additions & 2 deletions
README.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
Expand Down

1 change: 1 addition & 0 deletions
tests/conftest.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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change: add MXNet 1.4.1 support#886

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laurenyu
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change: add MXNet 1.4.1 support
#886
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5c05ec4

update docs


laurenyu Jun 24, 2019
435819d

update pytest fixture


laurenyu Jun 24, 2019
e214ae4

bump LATEST_VERSION


laurenyu Jul 3, 2019
00011ec

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
a02e488

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
715e202

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019
7352f5f

Merge branch 'master' into mx-1.4.1


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4 changes: 2 additions & 2 deletions
README.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
Expand Down

2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
Expand Down

1 change: 1 addition & 0 deletions
tests/conftest.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
Expand Down

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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change: add MXNet 1.4.1 support#886

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 Merged

laurenyu
merged 7 commits into

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Jul 18, 2019
 Merged


change: add MXNet 1.4.1 support
#886
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5c05ec4

update docs


laurenyu Jun 24, 2019
435819d

update pytest fixture


laurenyu Jun 24, 2019
e214ae4

bump LATEST_VERSION


laurenyu Jul 3, 2019
00011ec

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
a02e488

Merge branch 'master' into mx-1.4.1


laurenyu Jul 3, 2019
715e202

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019
7352f5f

Merge branch 'master' into mx-1.4.1


laurenyu Jul 18, 2019

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4 changes: 2 additions & 2 deletions
README.rst

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Original file line numberDiff line numberDiff line change
Expand Up@@ -173,9 +173,9 @@ MXNet SageMaker Estimators

By using MXNet SageMaker Estimators, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

We recommend that you use the latest supported version, because that's where we focus most of our development efforts.

Expand Down

32 changes: 16 additions & 16 deletions
doc/using_mxnet.rst

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -6,9 +6,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

Training with MXNet
-------------------
Expand DownExpand Up@@ -806,23 +806,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
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32 changes: 16 additions & 16 deletions
src/sagemaker/mxnet/README.rst

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Expand Up@@ -4,9 +4,9 @@ Using MXNet with the SageMaker Python SDK

With the SageMaker Python SDK, you can train and host MXNet models on Amazon SageMaker.

Supported versions of MXNet: ``1.4.0``, ``1.3.0``, ``1.2.1``, ``1.1.0``, ``1.0.0``, ``0.12.1``.
Supported versions of MXNet: ``0.12.1``, ``1.0.0``, ``1.1.0``, ``1.2.1``, ``1.3.0``, ``1.4.0``, ``1.4.1``.

Supported versions of MXNet for Elastic Inference: ``1.4.0``, ``1.3.0``.
Supported versions of MXNet for Elastic Inference: ``1.3.0``, ``1.4.0``, ``1.4.1``.

For information about using MXNet with the SageMaker Python SDK, see https://sagemaker.readthedocs.io/en/stable/using_mxnet.html.

Expand All@@ -21,23 +21,23 @@ Your MXNet training script will be run on version 1.2.1 by default. (See below f

The Docker images have the following dependencies installed:

+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Dependencies | MXNet 0.12.1 | MXNet 1.0.0 | MXNet 1.1.0 | MXNet 1.2.1 | MXNet 1.3.0 | MXNet 1.4.0 | MXNet 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| Python | 2.7 or 3.5 | 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.5| 2.7 or 3.6| 2.7 or 3.6|
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| CUDA (GPU image only) | 9.0 | 9.0 | 9.0 | 9.0 | 9.0 | 9.2 | 10.0 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| numpy | 1.13.3 | 1.13.3 | 1.13.3 | 1.14.5 | 1.14.6 | 1.16.3 | 1.14.5 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| onnx | N/A | N/A | N/A | 1.2.1 | 1.2.1 | 1.4.1 | 1.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+
| keras-mxnet | N/A | N/A | N/A | N/A | 2.2.2 | 2.2.4.1 | 2.2.4.1 |
+-------------------------+--------------+-------------+-------------+-------------+-------------+-------------+-------------+

The Docker images extend Ubuntu 16.04.

You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.2``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.2.1.
You can select version of MXNet by passing a ``framework_version`` keyword arg to the MXNet Estimator constructor. Currently supported versions are listed in the above table. You can also set ``framework_version`` to only specify major and minor version, e.g ``1.4``, which will cause your training script to be run on the latest supported patch version of that minor version, which in this example would be 1.4.1.
Alternatively, you can build your own image by following the instructions in the SageMaker MXNet containers repository, and passing ``image_name`` to the MXNet Estimator constructor.

You can visit the SageMaker MXNet container repositories here:
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2 changes: 1 addition & 1 deletion
src/sagemaker/mxnet/estimator.py

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Expand Up@@ -34,7 +34,7 @@ class MXNet(Framework):
 __framework_name__ = "mxnet"
 _LOWEST_SCRIPT_MODE_VERSION = ["1", "3"]

 LATEST_VERSION = "1.4"
 LATEST_VERSION = "1.4.1"
 """The latest version of MXNet included in the SageMaker pre-built Docker images."""

 def __init__(
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tests/conftest.py

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Expand Up@@ -135,6 +135,7 @@ def chainer_version(request):
 "1.3.0",
 "1.4",
 "1.4.0",
 "1.4.1",
 ],
)
def mxnet_version(request):
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