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How to use current_scope method in Slash

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arg_scope.py

Source:arg_scope.py

1# Copyright 2016 The TensorFlow Authors. All Rights Reserved.2#3# Licensed under the Apache License, Version 2.0 (the "License");4# you may not use this file except in compliance with the License.5# You may obtain a copy of the License at6#7#     http://www.apache.org/licenses/LICENSE-2.08#9# Unless required by applicable law or agreed to in writing, software10# distributed under the License is distributed on an "AS IS" BASIS,11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.12# See the License for the specific language governing permissions and13# limitations under the License.14# ==============================================================================15"""Contains the arg_scope used for scoping layers arguments.16  Allows one to define models much more compactly by eliminating boilerplate17  code. This is accomplished through the use of argument scoping (arg_scope).18  Example of how to use tf.contrib.framework.arg_scope:19  ```20  from third_party.tensorflow.contrib.layers.python import layers21  arg_scope = tf.contrib.framework.arg_scope22  with arg_scope([layers.conv2d], padding='SAME',23                 initializer=layers.variance_scaling_initializer(),24                 regularizer=layers.l2_regularizer(0.05)):25    net = layers.conv2d(inputs, 64, [11, 11], 4, padding='VALID', scope='conv1')26    net = layers.conv2d(net, 256, [5, 5], scope='conv2')27  ```28  The first call to conv2d will behave as follows:29    layers.conv2d(inputs, 64, [11, 11], 4, padding='VALID',30                  initializer=layers.variance_scaling_initializer(),31                  regularizer=layers.l2_regularizer(0.05), scope='conv1')32  The second call to conv2d will also use the arg_scope's default for padding:33    layers.conv2d(inputs, 256, [5, 5], padding='SAME',34                  initializer=layers.variance_scaling_initializer(),35                  regularizer=layers.l2_regularizer(0.05), scope='conv2')36  Example of how to reuse an arg_scope:37  ```38  with arg_scope([layers.conv2d], padding='SAME',39                 initializer=layers.variance_scaling_initializer(),40                 regularizer=layers.l2_regularizer(0.05)) as sc:41    net = layers.conv2d(net, 256, [5, 5], scope='conv1')42    ....43  with arg_scope(sc):44    net = layers.conv2d(net, 256, [5, 5], scope='conv2')45  ```46  Example of how to use tf.contrib.framework.add_arg_scope to enable your47  function to be called within an arg_scope later:48  @tf.contrib.framework.add_arg_scope49  def conv2d(*args, **kwargs)50"""51from __future__ import absolute_import52from __future__ import division53from __future__ import print_function54from tensorflow.python.util import tf_contextlib55from tensorflow.python.util import tf_decorator56__all__ = [57    'arg_scope', 'add_arg_scope', 'current_arg_scope', 'has_arg_scope',58    'arg_scoped_arguments', 'arg_scope_func_key'59]60_ARGSTACK = [{}]61_DECORATED_OPS = {}62def _get_arg_stack():63  if _ARGSTACK:64    return _ARGSTACK65  else:66    _ARGSTACK.append({})67    return _ARGSTACK68def current_arg_scope():69  stack = _get_arg_stack()70  return stack[-1]71def arg_scope_func_key(op):72  return getattr(op, '_key_op', str(op))73def _name_op(op):74  return (op.__module__, op.__name__)75def _kwarg_names(func):76  kwargs_length = len(func.__defaults__) if func.__defaults__ else 077  return func.__code__.co_varnames[-kwargs_length:func.__code__.co_argcount]78def _add_op(op):79  key_op = arg_scope_func_key(op)80  _DECORATED_OPS[key_op] = _kwarg_names(op)81@tf_contextlib.contextmanager82def arg_scope(list_ops_or_scope, **kwargs):83  """Stores the default arguments for the given set of list_ops.84  For usage, please see examples at top of the file.85  Args:86    list_ops_or_scope: List or tuple of operations to set argument scope for or87      a dictionary containing the current scope. When list_ops_or_scope is a88      dict, kwargs must be empty. When list_ops_or_scope is a list or tuple,89      then every op in it need to be decorated with @add_arg_scope to work.90    **kwargs: keyword=value that will define the defaults for each op in91              list_ops. All the ops need to accept the given set of arguments.92  Yields:93    the current_scope, which is a dictionary of {op: {arg: value}}94  Raises:95    TypeError: if list_ops is not a list or a tuple.96    ValueError: if any op in list_ops has not be decorated with @add_arg_scope.97  """98  if isinstance(list_ops_or_scope, dict):99    # Assumes that list_ops_or_scope is a scope that is being reused.100    if kwargs:101      raise ValueError('When attempting to re-use a scope by suppling a'102                       'dictionary, kwargs must be empty.')103    current_scope = list_ops_or_scope.copy()104    try:105      _get_arg_stack().append(current_scope)106      yield current_scope107    finally:108      _get_arg_stack().pop()109  else:110    # Assumes that list_ops_or_scope is a list/tuple of ops with kwargs.111    if not isinstance(list_ops_or_scope, (list, tuple)):112      raise TypeError('list_ops_or_scope must either be a list/tuple or reused '113                      'scope (i.e. dict)')114    try:115      current_scope = current_arg_scope().copy()116      for op in list_ops_or_scope:117        key = arg_scope_func_key(op)118        if not has_arg_scope(op):119          raise ValueError('%s is not decorated with @add_arg_scope',120                           _name_op(op))121        if key in current_scope:122          current_kwargs = current_scope[key].copy()123          current_kwargs.update(kwargs)124          current_scope[key] = current_kwargs125        else:126          current_scope[key] = kwargs.copy()127      _get_arg_stack().append(current_scope)128      yield current_scope129    finally:130      _get_arg_stack().pop()131def add_arg_scope(func):132  """Decorates a function with args so it can be used within an arg_scope.133  Args:134    func: function to decorate.135  Returns:136    A tuple with the decorated function func_with_args().137  """138  def func_with_args(*args, **kwargs):139    current_scope = current_arg_scope()140    current_args = kwargs141    key_func = arg_scope_func_key(func)142    if key_func in current_scope:143      current_args = current_scope[key_func].copy()144      current_args.update(kwargs)145    return func(*args, **current_args)146  _add_op(func)147  setattr(func_with_args, '_key_op', arg_scope_func_key(func))148  return tf_decorator.make_decorator(func, func_with_args)149def has_arg_scope(func):150  """Checks whether a func has been decorated with @add_arg_scope or not.151  Args:152    func: function to check.153  Returns:154    a boolean.155  """156  return arg_scope_func_key(func) in _DECORATED_OPS157def arg_scoped_arguments(func):158  """Returns the list kwargs that arg_scope can set for a func.159  Args:160    func: function which has been decorated with @add_arg_scope.161  Returns:162    a list of kwargs names.163  """164  assert has_arg_scope(func)...

scopes.py

Source:scopes.py

1# Copyright 2016 Google Inc. All Rights Reserved.2#3# Licensed under the Apache License, Version 2.0 (the "License");4# you may not use this file except in compliance with the License.5# You may obtain a copy of the License at6#7# http://www.apache.org/licenses/LICENSE-2.08#9# Unless required by applicable law or agreed to in writing, software10# distributed under the License is distributed on an "AS IS" BASIS,11# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.12# See the License for the specific language governing permissions and13# limitations under the License.14# ==============================================================================15"""Contains the new arg_scope used for TF-Slim ops.16  Allows one to define models much more compactly by eliminating boilerplate17  code. This is accomplished through the use of argument scoping (arg_scope).18  Example of how to use scopes.arg_scope:19  with scopes.arg_scope(ops.conv2d, padding='SAME',20                      stddev=0.01, weight_decay=0.0005):21    net = ops.conv2d(inputs, 64, [11, 11], 4, padding='VALID', scope='conv1')22    net = ops.conv2d(net, 256, [5, 5], scope='conv2')23  The first call to conv2d will overwrite padding:24    ops.conv2d(inputs, 64, [11, 11], 4, padding='VALID',25              stddev=0.01, weight_decay=0.0005, scope='conv1')26  The second call to Conv will use predefined args:27    ops.conv2d(inputs, 256, [5, 5], padding='SAME',28               stddev=0.01, weight_decay=0.0005, scope='conv2')29  Example of how to reuse an arg_scope:30  with scopes.arg_scope(ops.conv2d, padding='SAME',31                      stddev=0.01, weight_decay=0.0005) as conv2d_arg_scope:32    net = ops.conv2d(net, 256, [5, 5], scope='conv1')33    ....34  with scopes.arg_scope(conv2d_arg_scope):35    net = ops.conv2d(net, 256, [5, 5], scope='conv2')36  Example of how to use scopes.add_arg_scope:37  @scopes.add_arg_scope38  def conv2d(*args, **kwargs)39"""40from __future__ import absolute_import41from __future__ import division42from __future__ import print_function43import contextlib44import functools45from tensorflow.python.framework import ops46_ARGSTACK_KEY = ("__arg_stack",)47_DECORATED_OPS = set()48def _get_arg_stack():49  stack = ops.get_collection(_ARGSTACK_KEY)50  if stack:51    return stack[0]52  else:53    stack = [{}]54    ops.add_to_collection(_ARGSTACK_KEY, stack)55    return stack56def _current_arg_scope():57  stack = _get_arg_stack()58  return stack[-1]59def _add_op(op):60  key_op = (op.__module__, op.__name__)61  if key_op not in _DECORATED_OPS:62    _DECORATED_OPS.add(key_op)63@contextlib.contextmanager64def arg_scope(list_ops_or_scope, **kwargs):65  """Stores the default arguments for the given set of list_ops.66  For usage, please see examples at top of the file.67  Args:68    list_ops_or_scope: List or tuple of operations to set argument scope for or69      a dictionary containg the current scope. When list_ops_or_scope is a dict,70      kwargs must be empty. When list_ops_or_scope is a list or tuple, then71      every op in it need to be decorated with @add_arg_scope to work.72    **kwargs: keyword=value that will define the defaults for each op in73              list_ops. All the ops need to accept the given set of arguments.74  Yields:75    the current_scope, which is a dictionary of {op: {arg: value}}76  Raises:77    TypeError: if list_ops is not a list or a tuple.78    ValueError: if any op in list_ops has not be decorated with @add_arg_scope.79  """80  if isinstance(list_ops_or_scope, dict):81    # Assumes that list_ops_or_scope is a scope that is being reused.82    if kwargs:83      raise ValueError("When attempting to re-use a scope by suppling a"84                       "dictionary, kwargs must be empty.")85    current_scope = list_ops_or_scope.copy()86    try:87      _get_arg_stack().append(current_scope)88      yield current_scope89    finally:90      _get_arg_stack().pop()91  else:92    # Assumes that list_ops_or_scope is a list/tuple of ops with kwargs.93    if not isinstance(list_ops_or_scope, (list, tuple)):94      raise TypeError("list_ops_or_scope must either be a list/tuple or reused"95                      "scope (i.e. dict)")96    try:97      current_scope = _current_arg_scope().copy()98      for op in list_ops_or_scope:99        key_op = (op.__module__, op.__name__)100        if not has_arg_scope(op):101          raise ValueError("%s is not decorated with @add_arg_scope", key_op)102        if key_op in current_scope:103          current_kwargs = current_scope[key_op].copy()104          current_kwargs.update(kwargs)105          current_scope[key_op] = current_kwargs106        else:107          current_scope[key_op] = kwargs.copy()108      _get_arg_stack().append(current_scope)109      yield current_scope110    finally:111      _get_arg_stack().pop()112def add_arg_scope(func):113  """Decorates a function with args so it can be used within an arg_scope.114  Args:115    func: function to decorate.116  Returns:117    A tuple with the decorated function func_with_args().118  """119  @functools.wraps(func)120  def func_with_args(*args, **kwargs):121    current_scope = _current_arg_scope()122    current_args = kwargs123    key_func = (func.__module__, func.__name__)124    if key_func in current_scope:125      current_args = current_scope[key_func].copy()126      current_args.update(kwargs)127    return func(*args, **current_args)128  _add_op(func)129  return func_with_args130def has_arg_scope(func):131  """Checks whether a func has been decorated with @add_arg_scope or not.132  Args:133    func: function to check.134  Returns:135    a boolean.136  """137  key_op = (func.__module__, func.__name__)...

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