87 lines
3.7 KiB
Python
87 lines
3.7 KiB
Python
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# Copyright 2017 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ==============================================================================
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"""TensorFlow Summary API v2.
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The operations in this package are safe to use with eager execution turned on or
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off. It has a more flexible API that allows summaries to be written directly
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from ops to places other than event log files, rather than propagating protos
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from @{tf.summary.merge_all} to @{tf.summary.FileWriter}.
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To use with eager execution enabled, write your code as follows:
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```python
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global_step = tf.train.get_or_create_global_step()
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summary_writer = tf.contrib.summary.create_file_writer(
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train_dir, flush_millis=10000)
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with summary_writer.as_default(), tf.contrib.summary.always_record_summaries():
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# model code goes here
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# and in it call
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tf.contrib.summary.scalar("loss", my_loss)
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# In this case every call to tf.contrib.summary.scalar will generate a record
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# ...
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```
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To use it with graph execution, write your code as follows:
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```python
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global_step = tf.train.get_or_create_global_step()
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summary_writer = tf.contrib.summary.create_file_writer(
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train_dir, flush_millis=10000)
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with summary_writer.as_default(), tf.contrib.summary.always_record_summaries():
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# model definition code goes here
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# and in it call
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tf.contrib.summary.scalar("loss", my_loss)
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# In this case every call to tf.contrib.summary.scalar will generate an op,
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# note the need to run tf.contrib.summary.all_summary_ops() to make sure these
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# ops get executed.
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# ...
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train_op = ....
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with tf.Session(...) as sess:
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tf.global_variables_initializer().run()
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tf.contrib.summary.initialize(graph=tf.get_default_graph())
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# ...
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while not_done_training:
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sess.run([train_op, tf.contrib.summary.all_summary_ops()])
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# ...
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```
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"""
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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# pylint: disable=unused-import
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from tensorflow.python.ops.summary_ops_v2 import all_summary_ops
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from tensorflow.python.ops.summary_ops_v2 import always_record_summaries
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from tensorflow.python.ops.summary_ops_v2 import audio
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from tensorflow.python.ops.summary_ops_v2 import create_db_writer
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from tensorflow.python.ops.summary_ops_v2 import create_file_writer
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from tensorflow.python.ops.summary_ops_v2 import create_summary_file_writer
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from tensorflow.python.ops.summary_ops_v2 import eval_dir
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from tensorflow.python.ops.summary_ops_v2 import flush
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from tensorflow.python.ops.summary_ops_v2 import generic
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from tensorflow.python.ops.summary_ops_v2 import graph
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from tensorflow.python.ops.summary_ops_v2 import histogram
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from tensorflow.python.ops.summary_ops_v2 import image
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from tensorflow.python.ops.summary_ops_v2 import import_event
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from tensorflow.python.ops.summary_ops_v2 import initialize
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from tensorflow.python.ops.summary_ops_v2 import never_record_summaries
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from tensorflow.python.ops.summary_ops_v2 import record_summaries_every_n_global_steps
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from tensorflow.python.ops.summary_ops_v2 import scalar
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from tensorflow.python.ops.summary_ops_v2 import should_record_summaries
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from tensorflow.python.ops.summary_ops_v2 import summary_writer_initializer_op
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from tensorflow.python.ops.summary_ops_v2 import SummaryWriter
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