Remove old doc generator.

Change: 150372607

1 files changed, 0 insertions, 332 deletions

diff --git a/tensorflow/python/framework/gen_docs_combined.py b/tensorflow/python/framework/gen_docs_combined.py
deleted file mode 100644
index 65379dda20..0000000000
--- a/tensorflow/python/framework/gen_docs_combined.py
+++ /dev/null
@@ -1,332 +0,0 @@
-# Copyright 2015 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.
-# ==============================================================================
-
-"""Updates generated docs from Python doc comments."""
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import argparse
-import collections
-import os.path
-import sys
-
-import tensorflow as tf
-
-from tensorflow.contrib import ffmpeg
-from tensorflow.python import debug as tf_debug
-from tensorflow.python.client import client_lib
-from tensorflow.python.framework import constant_op
-from tensorflow.python.framework import docs
-from tensorflow.python.framework import framework_lib
-
-FLAGS = None
-
-
-PREFIX_TEXT = """
-Note: Functions taking `Tensor` arguments can also take anything accepted by
-@{tf.convert_to_tensor}.
-"""
-
-
-def module_names():
-  return [
-      "tf",
-      "tf.errors",
-      "tf.image",
-      "tf.nn",
-      "tf.train",
-      "tf.python_io",
-      "tf.saved_model",
-      "tf.summary",
-      "tf.test",
-      "tf.contrib.bayesflow.entropy",
-      "tf.contrib.bayesflow.monte_carlo",
-      "tf.contrib.bayesflow.stochastic_graph",
-      "tf.contrib.bayesflow.stochastic_tensor",
-      "tf.contrib.bayesflow.variational_inference",
-      "tf.contrib.copy_graph",
-      "tf.contrib.crf",
-      "tf.contrib.distributions",
-      "tf.contrib.distributions.bijector",
-      "tf.contrib.ffmpeg",
-      "tf.contrib.framework",
-      "tf.contrib.graph_editor",
-      "tf.contrib.integrate",
-      "tf.contrib.layers",
-      "tf.contrib.learn",
-      "tf.contrib.learn.monitors",
-      "tf.contrib.legacy_seq2seq",
-      "tf.contrib.linalg",
-      "tf.contrib.losses",
-      "tf.contrib.metrics",
-      "tf.contrib.opt",
-      "tf.contrib.rnn",
-      "tf.contrib.solvers",
-      "tf.contrib.training",
-      "tf.contrib.util",
-      "tf_debug",
-  ]
-
-
-def find_module(base_module, name):
-  if name == "tf":
-    return base_module
-  # Special case for ffmpeg is needed since it's not linked in by default due
-  # to size concerns.
-  elif name == "tf.contrib.ffmpeg":
-    return ffmpeg
-  elif name == "tf_debug":
-    return tf_debug
-  elif name.startswith("tf."):
-    subname = name[3:]
-    subnames = subname.split(".")
-    parent_module = base_module
-    for s in subnames:
-      if not hasattr(parent_module, s):
-        raise ValueError(
-            "Module not found: {}. Submodule {} not found in parent module {}."
-            " Possible candidates are {}".format(
-                name, s, parent_module.__name__, dir(parent_module)))
-      parent_module = getattr(parent_module, s)
-    return parent_module
-  else:
-    raise ValueError(
-        "Invalid module name: {}. Module names must start with 'tf.'".format(
-            name))
-
-
-def get_module_to_name(names):
-  return collections.OrderedDict([(find_module(tf, x), x) for x in names])
-
-
-def all_libraries(module_to_name, members, documented):
-  """Make a list of the individual files that we want to create.
-
-  Args:
-    module_to_name: Dictionary mapping modules to short names.
-    members: Dictionary mapping member name to (fullname, member).
-    documented: Set of documented names to update.
-
-  Returns:
-    List of (filename, docs.Library) pairs.
-  """
-  def library(name, title, module=None, **args):
-    if module is None:
-      module = sys.modules["tensorflow.python.ops." + name]
-    return (name + ".md", docs.Library(title=title,
-                                       module_to_name=module_to_name,
-                                       members=members,
-                                       documented=documented,
-                                       module=module,
-                                       **args))
-  return collections.OrderedDict([
-      # Splits of module 'tf'.
-      library("framework", "Building Graphs", framework_lib),
-      library("check_ops", "Asserts and boolean checks."),
-      library("constant_op", "Constants, Sequences, and Random Values",
-              constant_op, prefix=PREFIX_TEXT),
-      library("state_ops",
-              "Variables",
-              exclude_symbols=["create_partitioned_variables"],
-              prefix=PREFIX_TEXT),
-      library("array_ops",
-              "Tensor Transformations",
-              exclude_symbols=["list_diff"],
-              prefix=PREFIX_TEXT),
-      library("math_ops",
-              "Math",
-              exclude_symbols=["sparse_matmul", "arg_min", "arg_max",
-                               "lin_space", "sparse_segment_mean_grad"],
-              prefix=PREFIX_TEXT),
-      library("string_ops", "Strings",
-              prefix=PREFIX_TEXT),
-      library("histogram_ops", "Histograms"),
-      library("control_flow_ops", "Control Flow", prefix=PREFIX_TEXT),
-      library("functional_ops", "Higher Order Functions", prefix=PREFIX_TEXT),
-      library("tensor_array_ops", "TensorArray Operations", prefix=PREFIX_TEXT),
-      library("session_ops", "Tensor Handle Operations", prefix=PREFIX_TEXT),
-      library("image", "Images", tf.image, exclude_symbols=["ResizeMethod"],
-              prefix=PREFIX_TEXT),
-      library("sparse_ops",
-              "Sparse Tensors",
-              exclude_symbols=["serialize_sparse", "serialize_many_sparse",
-                               "deserialize_many_sparse"],
-              prefix=PREFIX_TEXT),
-      library("io_ops",
-              "Inputs and Readers",
-              exclude_symbols=["LookupTableBase", "HashTable",
-                               "initialize_all_tables",
-                               "tables_initializer",
-                               "parse_single_sequence_example",
-                               "string_to_hash_bucket"],
-              prefix=PREFIX_TEXT),
-      library("python_io", "Data IO (Python functions)", tf.python_io),
-      library("nn",
-              "Neural Network",
-              tf.nn,
-              exclude_symbols=["conv2d_backprop_input",
-                               "conv2d_backprop_filter", "avg_pool_grad",
-                               "max_pool_grad", "max_pool_grad_with_argmax",
-                               "batch_norm_with_global_normalization_grad",
-                               "lrn_grad", "relu6_grad", "softplus_grad",
-                               "softsign_grad", "xw_plus_b", "relu_layer",
-                               "lrn", "batch_norm_with_global_normalization",
-                               "batch_norm_with_global_normalization_grad",
-                               "all_candidate_sampler", "seq2seq"],
-              prefix=PREFIX_TEXT),
-      library("client", "Running Graphs", client_lib),
-      library("train",
-              "Training",
-              tf.train,
-              exclude_symbols=["Feature", "Features", "BytesList", "FloatList",
-                               "Int64List", "Example", "InferenceExample",
-                               "FeatureList", "FeatureLists", "RankingExample",
-                               "SequenceExample"]),
-      library("script_ops",
-              "Wraps python functions",
-              prefix=PREFIX_TEXT),
-      library("summary", "Summary Operations", tf.summary),
-      library("test", "Testing", tf.test),
-      library("contrib.bayesflow.entropy",
-              "BayesFlow Entropy (contrib)",
-              tf.contrib.bayesflow.entropy),
-      library("contrib.bayesflow.monte_carlo",
-              "BayesFlow Monte Carlo (contrib)",
-              tf.contrib.bayesflow.monte_carlo),
-      library("contrib.bayesflow.stochastic_graph",
-              "BayesFlow Stochastic Graph (contrib)",
-              tf.contrib.bayesflow.stochastic_graph),
-      library("contrib.bayesflow.stochastic_tensor",
-              "BayesFlow Stochastic Tensors (contrib)",
-              tf.contrib.bayesflow.stochastic_tensor),
-      library("contrib.bayesflow.variational_inference",
-              "BayesFlow Variational Inference (contrib)",
-              tf.contrib.bayesflow.variational_inference),
-      library("contrib.crf", "CRF (contrib)", tf.contrib.crf),
-      library("contrib.distributions", "Statistical Distributions (contrib)",
-              tf.contrib.distributions),
-      library("contrib.distributions.bijector",
-              "Random variable transformations (contrib)",
-              tf.contrib.distributions.bijector),
-      library("contrib.ffmpeg", "FFmpeg (contrib)", ffmpeg),
-      library("contrib.framework", "Framework (contrib)", tf.contrib.framework),
-      library("contrib.graph_editor", "Graph Editor (contrib)",
-              tf.contrib.graph_editor),
-      library("contrib.integrate", "Integrate (contrib)", tf.contrib.integrate),
-      library("contrib.layers", "Layers (contrib)", tf.contrib.layers),
-      library("contrib.learn", "Learn (contrib)", tf.contrib.learn),
-      library("contrib.learn.monitors", "Monitors (contrib)",
-              tf.contrib.learn.monitors),
-      library("contrib.legacy_seq2seq", "Sequence to Sequence (contrib)",
-              tf.contrib.legacy_seq2seq),
-      library("contrib.linalg", "Linear Algebra (contrib)",
-              tf.contrib.linalg),
-      library("contrib.losses", "Losses (contrib)", tf.contrib.losses),
-      library("contrib.opt", "Optimization (contrib)", tf.contrib.opt),
-      library("contrib.rnn", "RNN and Cells (contrib)", tf.contrib.rnn),
-      library("contrib.metrics", "Metrics (contrib)", tf.contrib.metrics),
-      library("contrib.training", "Training (contrib)", tf.contrib.training),
-      library("contrib.util", "Utilities (contrib)", tf.contrib.util),
-      library("contrib.copy_graph", "Copying Graph Elements (contrib)",
-              tf.contrib.copy_graph),
-      library("tf_debug", "TensorFlow Debugger", tf_debug),
-  ])
-
-_hidden_symbols = ["Event", "LogMessage", "Summary", "SessionLog", "xrange",
-                   "HistogramProto", "ConfigProto", "NodeDef", "GraphDef",
-                   "GPUOptions", "GraphOptions", "RunOptions", "RunMetadata",
-                   "SessionInterface", "BaseSession", "NameAttrList",
-                   "AttrValue", "OptimizerOptions",
-                   "CollectionDef", "MetaGraphDef", "QueueRunnerDef",
-                   "SaverDef", "VariableDef", "TestCase", "GrpcServer",
-                   "ClusterDef", "JobDef", "ServerDef", "TensorInfo"]
-
-# TODO(skleinfeld, deannarubin) Address shortname
-# conflict between tf.contrib.learn.NanLossDuringTrainingError and
-# tf.contrib.learn.monitors.NanLossDuringTrainingError, arising due
-# to imports in learn/python/learn/__init__.py
-# TODO(wicke): Remove contrib.layers.relu* after shortnames are
-# disabled.  These conflict with tf.nn.relu*
-EXCLUDE = frozenset(["tf.contrib.learn.monitors.NanLossDuringTrainingError",
-                     "tf.contrib.layers.dropout",
-                     "tf.contrib.layers.bias_add",
-                     "tf.contrib.layers.conv2d",
-                     "tf.contrib.layers.conv2d_transpose",
-                     "tf.contrib.layers.separable_conv2d",
-                     "tf.contrib.layers.softmax",
-                     "tf.contrib.layers.relu", "tf.contrib.layers.relu6",
-                     "tf.contrib.framework.assert_global_step",
-                     "tf.contrib.framework.get_global_step",
-                     "tf.contrib.learn.NanLossDuringTrainingError",
-                     "tf.contrib.layers.stack",
-                     "tf.contrib.layers.ProblemType",
-                     "tf.confusion_matrix"])
-
-
-def main(unused_argv):
-  if not FLAGS.out_dir:
-    tf.logging.error("out_dir not specified")
-    return -1
-
-  # Document libraries
-  documented = set()
-  module_to_name = get_module_to_name(module_names())
-  members = docs.collect_members(module_to_name, exclude=EXCLUDE)
-  libraries = all_libraries(module_to_name, members, documented).items()
-
-  # Define catch_all library before calling write_libraries to avoid complaining
-  # about generically hidden symbols.
-  catch_all = docs.Library(title="Catch All", module=None,
-                           exclude_symbols=_hidden_symbols,
-                           module_to_name=module_to_name, members=members,
-                           documented=documented)
-
-  # Write docs to files
-  docs.write_libraries(FLAGS.out_dir, libraries)
-
-  # Make it easy to search for hidden symbols
-  if FLAGS.print_hidden_regex:
-    hidden = set(_hidden_symbols)
-    for _, lib in libraries:
-      hidden.update(lib.exclude_symbols)
-    print(r"hidden symbols regex = r'\b(%s)\b'" % "|".join(sorted(hidden)))
-
-  # Verify that all symbols are mentioned in some library doc.
-  catch_all.assert_no_leftovers()
-
-  # Generate index
-  with open(os.path.join(FLAGS.out_dir, "index.md"), "w") as f:
-    docs.Index(module_to_name, members, libraries,
-               "../../api_docs/python/").write_markdown_to_file(f)
-
-
-if __name__ == "__main__":
-  parser = argparse.ArgumentParser()
-  parser.register("type", "bool", lambda v: v.lower() == "true")
-  parser.add_argument(
-      "--out_dir",
-      type=str,
-      default=None,
-      help="Directory to which docs should be written.")
-  parser.add_argument(
-      "--print_hidden_regex",
-      type="bool",
-      nargs="?",
-      const=True,
-      default=False,
-      help="Dump a regular expression matching any hidden symbol")
-  FLAGS, unparsed = parser.parse_known_args()
-  tf.app.run(main=main, argv=[sys.argv[0]] + unparsed)