change: update v2 migration tool to rename TFS classes/imports#1552

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laurenyu merged 1 commit into from
Jun 8, 2020
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change: update v2 migration tool to rename TFS classes/imports #1552

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39 changes: 39 additions & 0 deletions src/sagemaker/cli/compatibility/v2/ast_transformer.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
"""An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

ast.fix_missing_locations(node)
return node

def visit_Import(self, node):
"""Visits an ``ast.Import`` node and returns a modified node, if needed.
See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

Args:
node (ast.Import): a node that represents an import statement.

Returns:
ast.Import: a node that represents an import statement, which has
potentially been modified from the original input.
"""
for import_checker in IMPORT_MODIFIERS:
import_checker.check_and_modify_node(node)

ast.fix_missing_locations(node)
return node

def visit_ImportFrom(self, node):
"""Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

Args:
node (ast.ImportFrom): a node that represents an import statement.

Returns:
ast.ImportFrom: a node that represents an import statement, which has
potentially been modified from the original input.
"""
for import_checker in IMPORT_FROM_MODIFIERS:
import_checker.check_and_modify_node(node)

ast.fix_missing_locations(node)
return node
1 change: 1 addition & 0 deletions src/sagemaker/cli/compatibility/v2/modifiers/__init__.py
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Expand Up@@ -17,4 +17,5 @@
deprecated_params,
framework_version,
tf_legacy_mode,
tfs,
)
121 changes: 121 additions & 0 deletions src/sagemaker/cli/compatibility/v2/modifiers/tfs.py
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@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
"""A class to rename TensorFlow Serving classes."""

def node_should_be_modified(self, node):
"""Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

This looks for the following calls:

- ``sagemaker.tensorflow.serving.Model``
- ``sagemaker.tensorflow.serving.Predictor``
- ``Predictor``

Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
for indicating a TFS Model object.

Args:
node (ast.Call): a node that represents a function call. For more,
see https://docs.python.org/3/library/ast.html#abstract-grammar.

Returns:
bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
"""
if isinstance(node.func, ast.Name):
return node.func.id == "Predictor"

if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
return False

return (
isinstance(node.func.value, ast.Attribute)
and node.func.value.attr == "serving"
and isinstance(node.func.value.value, ast.Attribute)
and node.func.value.value.attr == "tensorflow"
and isinstance(node.func.value.value.value, ast.Name)
and node.func.value.value.value.id == "sagemaker"
)

def modify_node(self, node):
"""Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

- ``sagemaker.tensorflow.TensorFlowModel``
- ``sagemaker.tensorflow.TensorFlowPredictor``

Args:
node (ast.Call): a node that represents a TensorFlow Serving constructor.
"""
if isinstance(node.func, ast.Name):
node.func.id = self._new_cls_name(node.func.id)
else:
node.func.attr = self._new_cls_name(node.func.attr)
node.func.value = node.func.value.value

def _new_cls_name(self, cls_name):
"""Returns the v2 class name."""
return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
"""A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

def node_should_be_modified(self, node):
"""Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

Args:
node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

Returns:
bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
"""
return node.module == "sagemaker.tensorflow.serving"

def modify_node(self, node):
"""Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

Args:
node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
"""
node.module = "sagemaker.tensorflow"

for cls in node.names:
cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
"""A class to update ``import sagemaker.tensorflow.serving``."""

def check_and_modify_node(self, node):
"""Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
and, if so, changes it to ``sagemaker.tensorflow``.

Args:
node (ast.Import): a node that represents an import statement. For more,
see https://docs.python.org/3/library/ast.html#abstract-grammar.
"""
for module in node.names:
if module.name == "sagemaker.tensorflow.serving":
module.name = "sagemaker.tensorflow"
4 changes: 4 additions & 0 deletions tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py
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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
return pasta.parse(code).body[0].value


def ast_import(code):
return pasta.parse(code).body[0]
107 changes: 107 additions & 0 deletions tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py
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@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
tfs_constructors = (
"sagemaker.tensorflow.serving.Model()",
"sagemaker.tensorflow.serving.Predictor()",
"Predictor()",
)

modifier = tfs.TensorFlowServingConstructorRenamer()

for constructor in tfs_constructors:
node = ast_call(constructor)
assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
modifier = tfs.TensorFlowServingConstructorRenamer()
node = ast_call("Model()")
assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
modifier = tfs.TensorFlowServingConstructorRenamer()

node = ast_call("sagemaker.tensorflow.serving.Model()")
modifier.modify_node(node)
assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

node = ast_call("sagemaker.tensorflow.serving.Predictor()")
modifier.modify_node(node)
assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

node = ast_call("Predictor()")
modifier.modify_node(node)
assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
import_statements = (
"from sagemaker.tensorflow.serving import Model, Predictor",
"from sagemaker.tensorflow.serving import Predictor",
"from sagemaker.tensorflow.serving import Model as tfsModel",
)

modifier = tfs.TensorFlowServingImportFromRenamer()

for import_from in import_statements:
node = ast_import(import_from)
assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
modifier = tfs.TensorFlowServingImportFromRenamer()
node = ast_import("from sagemaker import Session")
assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
modifier = tfs.TensorFlowServingImportFromRenamer()

node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
modifier.modify_node(node)
expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
assert expected_result == pasta.dump(node)

node = ast_import("from sagemaker.tensorflow.serving import Predictor")
modifier.modify_node(node)
assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
modifier.modify_node(node)
assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
modifier = tfs.TensorFlowServingImportRenamer()
node = ast_import("import sagemaker.tensorflow.serving")
modifier.check_and_modify_node(node)
assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
modifier = tfs.TensorFlowServingImportRenamer()

import_statement = "import random"
node = ast_import(import_statement)
modifier.check_and_modify_node(node)
assert import_statement == pasta.dump(node)
, '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: update v2 migration tool to rename TFS classes/imports#1552

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 Merged

laurenyu
merged 1 commit into

from

Jun 8, 2020
 Merged


change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

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@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

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# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)

, '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");
}
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})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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change: update v2 migration tool to rename TFS classes/imports#1552

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change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

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@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)

, '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: update v2 migration tool to rename TFS classes/imports#1552

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 Merged

laurenyu
merged 1 commit into

from

Jun 8, 2020
 Merged


change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)

, '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: update v2 migration tool to rename TFS classes/imports#1552

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laurenyu
merged 1 commit into

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Jun 8, 2020
 Merged


change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)

, '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: update v2 migration tool to rename TFS classes/imports#1552

New issue

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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Sign in
to your account

 Merged

laurenyu
merged 1 commit into

from

Jun 8, 2020
 Merged


change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

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Open in desktop

Original file line numberDiff line numberDiff line change
@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)

, '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: update v2 migration tool to rename TFS classes/imports#1552

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laurenyu
merged 1 commit into

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Jun 8, 2020
 Merged


change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

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Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

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@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)

, '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: update v2 migration tool to rename TFS classes/imports#1552

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 Merged

laurenyu
merged 1 commit into

from

Jun 8, 2020
 Merged


change: update v2 migration tool to rename TFS classes/imports
#1552
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39 changes: 39 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/ast_transformer.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -22,8 +22,13 @@
 modifiers.tf_legacy_mode.TensorFlowLegacyModeConstructorUpgrader(),
 modifiers.tf_legacy_mode.TensorBoardParameterRemover(),
 modifiers.deprecated_params.TensorFlowScriptModeParameterRemover(),
 modifiers.tfs.TensorFlowServingConstructorRenamer(),
]

IMPORT_MODIFIERS = [modifiers.tfs.TensorFlowServingImportRenamer()]

IMPORT_FROM_MODIFIERS = [modifiers.tfs.TensorFlowServingImportFromRenamer()]


class ASTTransformer(ast.NodeTransformer):
 """An ``ast.NodeTransformer`` subclass that walks the abstract syntax tree and
Expand All@@ -46,3 +51,37 @@ def visit_Call(self, node):

 ast.fix_missing_locations(node)
 return node

 def visit_Import(self, node):
 """Visits an ``ast.Import`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.Import): a node that represents an import statement.

 Returns:
 ast.Import: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

 def visit_ImportFrom(self, node):
 """Visits an ``ast.ImportFrom`` node and returns a modified node, if needed.
 See https://docs.python.org/3/library/ast.html#ast.NodeTransformer.

 Args:
 node (ast.ImportFrom): a node that represents an import statement.

 Returns:
 ast.ImportFrom: a node that represents an import statement, which has
 potentially been modified from the original input.
 """
 for import_checker in IMPORT_FROM_MODIFIERS:
 import_checker.check_and_modify_node(node)

 ast.fix_missing_locations(node)
 return node

1 change: 1 addition & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/__init__.py

View file


Open in desktop

Original file line numberDiff line numberDiff line change
Expand Up@@ -17,4 +17,5 @@
 deprecated_params,
 framework_version,
 tf_legacy_mode,
 tfs,
)

121 changes: 121 additions & 0 deletions
src/sagemaker/cli/compatibility/v2/modifiers/tfs.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,121 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
"""Classes to modify TensorFlow Serving code to be compatible with SageMaker Python SDK v2."""
from __future__ import absolute_import

import ast

from sagemaker.cli.compatibility.v2.modifiers.modifier import Modifier


class TensorFlowServingConstructorRenamer(Modifier):
 """A class to rename TensorFlow Serving classes."""

 def node_should_be_modified(self, node):
 """Checks if the ``ast.Call`` node instantiates a TensorFlow Serving class.

 This looks for the following calls:

 - ``sagemaker.tensorflow.serving.Model``
 - ``sagemaker.tensorflow.serving.Predictor``
 - ``Predictor``

 Because ``Model`` can refer to either ``sagemaker.tensorflow.serving.Model``
 or :class:`~sagemaker.model.Model`, ``Model`` on its own is not sufficient
 for indicating a TFS Model object.

 Args:
 node (ast.Call): a node that represents a function call. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.Call`` instantiates a TensorFlow Serving class.
 """
 if isinstance(node.func, ast.Name):
 return node.func.id == "Predictor"

 if not (isinstance(node.func, ast.Attribute) and node.func.attr in ("Model", "Predictor")):
 return False

 return (
 isinstance(node.func.value, ast.Attribute)
 and node.func.value.attr == "serving"
 and isinstance(node.func.value.value, ast.Attribute)
 and node.func.value.value.attr == "tensorflow"
 and isinstance(node.func.value.value.value, ast.Name)
 and node.func.value.value.value.id == "sagemaker"
 )

 def modify_node(self, node):
 """Modifies the ``ast.Call`` node to use the v2 classes for TensorFlow Serving:

 - ``sagemaker.tensorflow.TensorFlowModel``
 - ``sagemaker.tensorflow.TensorFlowPredictor``

 Args:
 node (ast.Call): a node that represents a TensorFlow Serving constructor.
 """
 if isinstance(node.func, ast.Name):
 node.func.id = self._new_cls_name(node.func.id)
 else:
 node.func.attr = self._new_cls_name(node.func.attr)
 node.func.value = node.func.value.value

 def _new_cls_name(self, cls_name):
 """Returns the v2 class name."""
 return "TensorFlow{}".format(cls_name)


class TensorFlowServingImportFromRenamer(Modifier):
 """A class to update import statements starting with ``from sagemaker.tensorflow.serving``."""

 def node_should_be_modified(self, node):
 """Checks if the import statement imports from the ``sagemaker.tensorflow.serving`` module.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.

 Returns:
 bool: If the ``ast.ImportFrom`` uses the ``sagemaker.tensorflow.serving`` module.
 """
 return node.module == "sagemaker.tensorflow.serving"

 def modify_node(self, node):
 """Changes the ``ast.ImportFrom`` node's module to ``sagemaker.tensorflow`` and updates the
 imported class names to ``TensorFlowModel`` and ``TensorFlowPredictor``, as applicable.

 Args:
 node (ast.ImportFrom): a node that represents a ``from ... import ... `` statement.
 For more, see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 node.module = "sagemaker.tensorflow"

 for cls in node.names:
 cls.name = "TensorFlow{}".format(cls.name)


class TensorFlowServingImportRenamer(Modifier):
 """A class to update ``import sagemaker.tensorflow.serving``."""

 def check_and_modify_node(self, node):
 """Checks if the ``ast.Import`` node imports the ``sagemaker.tensorflow.serving`` module
 and, if so, changes it to ``sagemaker.tensorflow``.

 Args:
 node (ast.Import): a node that represents an import statement. For more,
 see https://docs.python.org/3/library/ast.html#abstract-grammar.
 """
 for module in node.names:
 if module.name == "sagemaker.tensorflow.serving":
 module.name = "sagemaker.tensorflow"

4 changes: 4 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/ast_converter.py

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Original file line numberDiff line numberDiff line change
Expand Up@@ -17,3 +17,7 @@

def ast_call(code):
 return pasta.parse(code).body[0].value


def ast_import(code):
 return pasta.parse(code).body[0]

107 changes: 107 additions & 0 deletions
tests/unit/sagemaker/cli/compatibility/v2/modifiers/test_tfs.py

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Original file line numberDiff line numberDiff line change
@@ -0,0 +1,107 @@
# Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License"). You
# may not use this file except in compliance with the License. A copy of
# the License is located at
#
# http://aws.amazon.com/apache2.0/
#
# or in the "license" file accompanying this file. This file is
# distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF
# ANY KIND, either express or implied. See the License for the specific
# language governing permissions and limitations under the License.
from __future__ import absolute_import

import pasta

from sagemaker.cli.compatibility.v2.modifiers import tfs
from tests.unit.sagemaker.cli.compatibility.v2.modifiers.ast_converter import ast_call, ast_import


def test_constructor_node_should_be_modified_tfs_constructor():
 tfs_constructors = (
 "sagemaker.tensorflow.serving.Model()",
 "sagemaker.tensorflow.serving.Predictor()",
 "Predictor()",
 )

 modifier = tfs.TensorFlowServingConstructorRenamer()

 for constructor in tfs_constructors:
 node = ast_call(constructor)
 assert modifier.node_should_be_modified(node) is True


def test_constructor_node_should_be_modified_random_function_call():
 modifier = tfs.TensorFlowServingConstructorRenamer()
 node = ast_call("Model()")
 assert modifier.node_should_be_modified(node) is False


def test_constructor_modify_node():
 modifier = tfs.TensorFlowServingConstructorRenamer()

 node = ast_call("sagemaker.tensorflow.serving.Model()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowModel()" == pasta.dump(node)

 node = ast_call("sagemaker.tensorflow.serving.Predictor()")
 modifier.modify_node(node)
 assert "sagemaker.tensorflow.TensorFlowPredictor()" == pasta.dump(node)

 node = ast_call("Predictor()")
 modifier.modify_node(node)
 assert "TensorFlowPredictor()" == pasta.dump(node)


def test_import_from_node_should_be_modified_tfs_module():
 import_statements = (
 "from sagemaker.tensorflow.serving import Model, Predictor",
 "from sagemaker.tensorflow.serving import Predictor",
 "from sagemaker.tensorflow.serving import Model as tfsModel",
 )

 modifier = tfs.TensorFlowServingImportFromRenamer()

 for import_from in import_statements:
 node = ast_import(import_from)
 assert modifier.node_should_be_modified(node) is True


def test_import_from_node_should_be_modified_random_import():
 modifier = tfs.TensorFlowServingImportFromRenamer()
 node = ast_import("from sagemaker import Session")
 assert modifier.node_should_be_modified(node) is False


def test_import_from_modify_node():
 modifier = tfs.TensorFlowServingImportFromRenamer()

 node = ast_import("from sagemaker.tensorflow.serving import Model, Predictor")
 modifier.modify_node(node)
 expected_result = "from sagemaker.tensorflow import TensorFlowModel, TensorFlowPredictor"
 assert expected_result == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Predictor")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowPredictor" == pasta.dump(node)

 node = ast_import("from sagemaker.tensorflow.serving import Model as tfsModel")
 modifier.modify_node(node)
 assert "from sagemaker.tensorflow import TensorFlowModel as tfsModel" == pasta.dump(node)


def test_import_check_and_modify_node_tfs_import():
 modifier = tfs.TensorFlowServingImportRenamer()
 node = ast_import("import sagemaker.tensorflow.serving")
 modifier.check_and_modify_node(node)
 assert "import sagemaker.tensorflow" == pasta.dump(node)


def test_import_check_and_modify_node_random_import():
 modifier = tfs.TensorFlowServingImportRenamer()

 import_statement = "import random"
 node = ast_import(import_statement)
 modifier.check_and_modify_node(node)
 assert import_statement == pasta.dump(node)