from tensorflow.contrib.py2tf import naming
from tensorflow.contrib.py2tf.convert import call_trees
from tensorflow.contrib.py2tf.convert import control_flow
-from tensorflow.contrib.py2tf.convert import gradients_function
from tensorflow.contrib.py2tf.convert import logical_expressions
from tensorflow.contrib.py2tf.convert import print_functions
from tensorflow.contrib.py2tf.convert import side_effect_guards
* deps: A set of strings, the fully qualified names of object
dependencies that this node has.
"""
- # TODO(mdan): Get rid of this.
- node = gradients_function.transform(node)
-
node = access.resolve(node)
node = live_values.resolve(node, namespace, config.PYTHON_LITERALS)
node = type_info.resolve(node, value_hints)
srcs = [
"call_trees.py",
"control_flow.py",
- "gradients_function.py",
"logical_expressions.py",
"print_functions.py",
"side_effect_guards.py",
],
)
-py_test(
- name = "gradients_function_test",
- srcs = ["gradients_function_test.py"],
- deps = [
- ":convert",
- "//tensorflow/contrib/eager/python:tfe",
- "//tensorflow/contrib/py2tf/pyct",
- "//tensorflow/contrib/py2tf/pyct/static_analysis",
- "//tensorflow/python:client_testlib",
- ],
-)
-
py_test(
name = "logical_expressions_test",
srcs = ["logical_expressions_test.py"],
+++ /dev/null
-# Copyright 2016 The TensorFlow Authors. 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.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Allows converting Eager-style gradients to graph versions."""
-# TODO(mdan): This is not needed. Remove once the static analysis works.
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import gast
-
-from tensorflow.contrib.py2tf.pyct import templates
-
-
-class GradientsFunctionTransformer(gast.NodeTransformer):
- """Hack: transforms eager-style gradients to TF compatible calls.
-
- Requires an expression of exactly this form:
- ... = tfe.value_and_gradients_function(...)(...)
- """
-
- # pylint:disable=invalid-name
-
- def visit_Assign(self, node):
- self.generic_visit(node)
-
- val = node.value
- if isinstance(val, gast.Call):
- if isinstance(val.func, gast.Call):
- if isinstance(val.func.func, gast.Attribute):
- if isinstance(val.func.func.value, gast.Name):
- if (val.func.func.value.id == 'tfe' and
- val.func.func.attr == 'value_and_gradients_function'):
-
- # pylint:disable=unused-argument,undefined-variable
-
- def template(loss_var, loss_fn, args, d_vars, wrt_vars):
- loss_var = loss_fn(args)
- d_vars = tf.gradients(loss_var, [wrt_vars])
-
- # pylint:enable=unused-argument,undefined-variable
-
- # How to get these values? Print out the node.
- loss_var = gast.Name(node.targets[0].elts[0].id, gast.Store(),
- None)
- loss_fn = gast.Name(val.func.args[0].id, gast.Load(), None)
- args = tuple(
- gast.Name(a.id, gast.Param(), None) for a in val.args)
- d_vars = node.targets[0].elts[1]
- wrt_vars = [val.args[e.n] for e in val.func.args[1].elts]
-
- node = templates.replace(
- template,
- loss_var=loss_var,
- loss_fn=loss_fn,
- args=args,
- d_vars=d_vars,
- wrt_vars=wrt_vars)
-
- return node
-
- # pylint:enable=invalid-name
-
-
-def transform(node):
- transformer = GradientsFunctionTransformer()
- node = transformer.visit(node)
- return node
+++ /dev/null
-# Copyright 2017 The TensorFlow Authors. 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.
-# You may obtain a copy of the License at
-#
-# http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Tests for gradients_function module."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-from tensorflow.contrib.eager.python import tfe
-from tensorflow.contrib.py2tf.convert import gradients_function
-from tensorflow.contrib.py2tf.pyct import compiler
-from tensorflow.contrib.py2tf.pyct import parser
-from tensorflow.python.framework import constant_op
-from tensorflow.python.ops import gradients_impl
-from tensorflow.python.platform import test
-
-
-class GradientsFunctionTest(test.TestCase):
-
- def test_transform(self):
-
- def loss(x, w):
- return x * w
-
- def test_fn(x, w):
- l, (dw,) = tfe.value_and_gradients_function(loss, [1])(x, w) # pylint:disable=undefined-variable
- return l, dw
-
- node = parser.parse_object(test_fn)
- node = gradients_function.transform(node)
- result = compiler.ast_to_object(node)
- setattr(result, 'tf', gradients_impl)
- setattr(result, 'loss', loss)
-
- with self.test_session() as sess:
- self.assertEqual(
- (12, 3),
- sess.run(
- result.test_fn(constant_op.constant(3), constant_op.constant(4))))
-
-
-if __name__ == '__main__':
- test.main()
projects / platform / upstream / tensorflow.git / commitdiff